Why Do Marketers Refrain from Budgeting for Marketing Measurement?

Why do marketers so often refrain from setting aside budget for marketing measurement?

It is fair to say that there is currently a very significant mismatch between the scale of the marketing measurement problem that marketers themselves acknowledge and the reality of how much money they normally put aside for remedying it.

On the one hand, we have 60% of marketers saying that internal stakeholders (perhaps the CFO), question their metrics, while 67% say that ROI proof is their top priority, when in reality only a small per cent actually put money aside for solving the problem.

Common Reasons Marketing Measurement Is Underfunded

There are many possible reasons why: they may expect their agency(ies) to produce the accurate ROI calculations they need at no cost, they may be thinking of doing it in-house, or they may simply not know how to go about it or how much to budget for it.

Why Agencies and In-House Teams Struggle With Measurement

The difficulty with the agency solution is that it’s then a case of their marking their own homework, and if trust is required, then an independent source of the truth is needed.

The problem with doing it in-house is that it requires both specialist technology and considerable statistical experience to get it right. The technology is required to deliver multi-touch attribution (MTA), where customer journeys, both online and offline, need to be joined together, and a weighting is made of the significance of each step in each journey.

Statistical skills are required to build the econometric models (MMMs) that are required to give a true view of the incremental effect of marketing.

How Much Budget Should Be Allocated to Marketing Measurement?

So, if the solution is to find an external marketing measurement provider, the question then becomes how much budget should be allowed for it?

There are no commonly available yardsticks, so we decided to put the question to Perplexity and received the following response:

Typical Benchmark Ranges for Marketing Measurement

  • Entry-level / basic tracking: 3–5% of media spend, usually covering web analytics, basic reporting, and limited attribution.
  • Standard performance-focused teams: 5–10% of media spend, funding proper multi-channel tracking, incrementality tests, and some external tools or light consultancy.
  • Advanced / data-driven marketers: 10–15% of media spend, where robust MMM, MTA, experiments, and specialist partners are used to drive continuous budget reallocation and ROMI gains.

What Marketers Actually Pay in Reality

However, our own experience as an external provider of marketing measurement services is significantly different. The following table gives an overview of the level of charges that in reality, we find marketers are prepared to pay:

Cost of marketing attribution as % of marketing budget

Complex marketing requires MMM + MTA 2.5% – 5.0% 1.0%
Simple marketing requires just MTA 1.0% – 2.5% 0.5%
  Low budget <1m High budget >10m


Here, we may be getting closer to understanding why marketers don’t budget for marketing measurement, which is because they fear it is going to cost too much.

Proving ROI From Marketing Measurement

Clearly, whatever is spent on marketing measurement needs to have its own ROI calculation, and this is where case studies are required to highlight examples of the returns obtained.

As no two businesses are the same, one cannot borrow an expected ROI from another company’s experience, but they do provide a level of benchmarking which may be useful:

Case Study: A Global Cruise Line

  • 50% improvement in ROI from a very significant spend in PPC
  • an accurate understanding of channel effectiveness in each region
  • a clear indication of which markets provided the highest potential

Case Study: A Large-Scale Wine Retailer

  • CMO obtained an increased marketing budget based on board-level confidence in the metrics he was using
  • The new customer acquisition strategy showed a 76% uplift in sales
  • CRM campaigns using direct mail and email were fine-tuned

Case Study: A Major Travel Company

  • £250k per annum saved on CFRM direct mail costs without loss of sales
  • CMO is able to justify his budget to the board
  • optimised budget allocation across channels

How Marketing Measurement Delivers ROI Across the Business

As you will see from these examples, there is no single area where marketing measurement will in reality provide better returns, as its impact will be felt across all channels and all customer segments.

However, in our experience, these are the more common ways in which measurements create their own ROI:

  • provision of a sound basis from which a CMO can justify their marketing budget, because the incremental effect is proven
  • an understanding of the impact over time of brand marketing and its contribution to other channels
  • optimising budget allocation across channels and also across different times of year
  • Reducing waste on campaigns that are not performing
  • provision of an understanding of which customer segments respond best to which types of marketing

Conclusion: Marketing Measurement Is an Investment, Not a Cost

In conclusion, marketers need not be fearful of the costs of using trustworthy independent providers of marketing measurement, because money spent in this way, rather than simply spending a tiny fraction more on media, can provide trust in what they are delivering, plus very significant returns, and can put the entire marketing activity on a sound ROI footing.

Common Attribution Mistakes in Multi-Channel Campaigns

evaluate your companys carbon emissions

Common attribution mistakes are costly, particularly when made repeatedly or over a long period. But there’s comfort in familiarity, and it’s not easy to break out of processes you have followed for such an extended time.

That doesn’t mean, however, you should settle for making those same errors campaign after campaign. Quite the opposite.

With every market becoming more competitive and customers no longer following a linear buying journey, it’s imperative to continuously improve your multi-channel attribution strategy.

As a provider of marketing attribution solutions, we’re primely positioned to see the common mistakes companies make, and more helpfully, to offer our advice on how to overcome them to save you from the bad habits that hinder your campaign and overall performance.

One can no longer afford to rely on processes that don’t serve the bigger picture.

marketing attribution reports

Mistake #1: Treating Marketing Channels in Isolation

Did you know that 7 out of 10 retail shoppers use multiple channels in their shopping journey? Data from a recent Uniform Market study shows that 73% of retail customers are omnichannel shoppers, engaging with an average of around 6 touchpoints before they finally decide to purchase.

They certainly channels don’t act in isolation, either. Rather, they’re interconnected and intertwined with one another, leading to a much more complex buying process.

Siloed reporting can lead to misattribution and inaccurate insight into the customer journey. If you narrow your vision to only one channel, you may miss out on the bigger picture of how your customers interact with your brand and make purchases.

This mistake can lead to:

  • Inaccurate allocation of marketing budget, i.e., under- or over-investing in the wrong channels based on incomplete data.
  • Inefficient strategies, as you may be focusing on channels that are not actually driving conversions.
  • Missed opportunities to optimise the customer journey.
  • Inconsistent messaging and branding across different channels, leading to confusion for customers.
  • Failing to identify and target potential high-value customers, resulting in missed ROI opportunities.

How to Avoid the Trap of Single-Channel Attribution

A holistic approach to attribution is the cure for such challenges.

It is by no means a simple change, as it requires a change to organisational culture, as well as the mindset of marketing and sales teams, but the rewards can be — and are — tremendous.

This requires implementing a new attribution model to your marketing strategies, one that takes into account all touchpoints and channels. This model should be based on data-driven insights and incorporate advanced analytics to accurately measure the impact of each event in the customer journey.

Learn More About Data-Driven Attribution

From this, all data from different sources can be integrated into one central system, allowing for a complete view of the customer and their interactions with your brand.

Direct marketing attribution

Mistake #2: Relying on GA4 for Tracking & Attribution

We understand that GA4 is the default tool for many organisations to track their website traffic and online behaviour. However, relying solely on GA4 for tracking and attribution can lead to incomplete or inaccurate data.

We’ve been making noise for a long time about the issues with GA4 for tracking, and it’s one of the most common attribution mistakes we see.

The truth is, using GA4 for tracking and attribution can create a distorted view of your customer journey.

The Limitations of GA4

We have an entire article delving into this discussion (which we recommend for a more complete reading), but here are just a few we’ve picked out below:

  • It’s blackbox — GA4 uses the same blackbox attribution rules carried over from Universal Analytics, meaning we simply have to trust the pre-defined models Google is utilising without being able to see or understand them for ourselves.
  • Ignores offline channels — GA4 does not account for the impact of offline channels (like in-store sales, phone calls, direct mail, door drops, etc.), which can lead to inaccurate attribution and missing out on important data.
  • Does not use first-party data — Google does not use first-party data or individual identifiers, which means it cannot be joined to other data sources and may miss out on valuable insights.
  • It’s not independent and always upweights the value contributed by Google media and products.

Read our full article on the limitations and alternatives to GA4 below.

Is There a GA4 Alternative? Yes, & It’s Here

In the same breath, other platform-reported data may also be limited in their scope and depth, such as Meta and TikTok, often overreporting on their own platforms and inflating performance.

Independent third-party data solutions can consolidate data from multiple sources and provide a more accurate, comprehensive, and unbiased view of your marketing efforts.

Unifida vs GA4

Mistake #3: Ignoring the Non-Linear Customer Journey

Customer journeys and the decision-making process were always intricate, but modern consumer behaviours are even more so.

A customer is not a number or a robot that follows the idealised path marketers have created. Instead, they bounce back and forth between different channels, devices, and touchpoints before coming to that precious purchase decision.

They’ll also carry out their own research beyond what your brand tells them — checking reviews, case studies, word-of-mouth recommendations, and more — to ensure they are making the right choice.

A customer’s first touchpoint with your brand may be through social media. They may see your new product ad while scrolling through their feeds, piquing their curiosity.

From there, they might visit your website on their mobile by using a non-branded search term. They may then visit your physical store to see the products in person.

They perhaps could then see that same initial social media ad, but on a different social platform, look at your Trustpilot reviews, go back to your website on their tablet by searching for your brand name, and then make a purchase.

Ignoring this non-linear customer journey is a grave mistake many businesses make. They stick to traditional marketing tactics and fail to adapt to the changing behaviours of today’s consumers.

Choosing to view customer journeys as linear can lead to:

  • Missed opportunities for engagement and conversions
  • Inaccurate data analysis and insights
  • Limited understanding of customers’ needs and preferences
  • Excluding specific customer segments from the overall marketing strategy
  • Creating a disconnect between the company and its customers

As consumers, we are becoming smarter, more aware, and more considered.

Consistent Branding & Messaging is the Key

In addition to implementing a customer journey-based attribution model that can track all these events, companies should focus on creating an omnichannel experience for their customers, providing a seamless and consistent experience across all channels, whether it’s through digital platforms or in-store interactions.

This could include:

  • Consistent branding and messaging across all channels
  • A unified approach to customer service
  • Personalisation based on user data and behaviour
  • Integration of data and insights from different channels to improve overall customer experience
  • Providing a variety of touchpoints for customers to engage with the brand, such as social media, email, live chat, etc.
  • Allowing customers to seamlessly switch between different channels without losing their progress or information
  • Utilising customer feedback and insights from various channels to continuously improve

A Single Customer View (SCV) is an essential tool for businesses to effectively manage their customer relationships. By integrating cross-channel data, an SCV provides a holistic view of the customer journey, allowing businesses to better understand and cater to their customers’ needs.

The What’s, Why’s & How’s of Building a Unified Customer View

happy customers

Mistake #4: Failing to Act on Attribution Insights

Another of the most repeated marketing attribution mistakes we come across is when organisations or marketing teams don’t strategically act upon the insights that attribution presents.

Even after implementing a robust and innovative attribution model, many do nothing with that data, or rather, they don’t know how to use it.

Change can be uncomfortable, as we all know, but choosing not to investigate or take action based on attribution insights is a great waste of time, effort, and resources.

By not utilising the data at your disposal, you risk:

  • Staying static while your competitors evolve and improve
  • Missing out on potential growth opportunities
  • Making uninformed decisions that could harm your business
  • Wasting budget on ineffective marketing channels
  • Frustrating and losing customers who feel ignored or undervalued
  • Falling behind in the industry and losing relevance

In a world where needs, wants, desires, aspirations, and preferences are constantly changing, it is crucial for businesses to stay updated and adapt accordingly.

Learning How to Take Action on Attribution

While we can’t provide you with a specific blueprint on how to take action on attribution, we can offer some general steps and points of reflection:

How to Act Upon Attribution Data What to Discuss & Ask
Consider what needs to change within your organisation Look at your current processes, systems, and culture…

Are there any areas that need improvement or realignment to better understand and utilise attribution?
Educate and involve all stakeholders Make sure everyone within your organisation is aware of the importance of attribution and their role.

Even if they’re not directly involved in attribution, their role will still be somewhat influenced by the changes that will inevitably occur.
Foster a culture of collaboration Attribution is not just about assigning credit, but also about working together towards common objectives.
Invest in technology This doesn’t just mean attribution technology, but also other software you may need to acquire to roll out new processes, such as project management tools, collaboration platforms, and communication software.

Automating processes can also help make attribution easier and more accurate.
Monitor and review Attribution is an ongoing process, so it’s important to regularly monitor and review your efforts.

This will not only highlight areas that may need improvement, but also allow you to track the success of your attribution strategy.

UniFida Can Support Your Attribution Reformation

The resources, time, and knowledge required for such a shift may be considerable, which is why UniFida’s Marketing Attribution Solution aims to simplify and streamline the process for businesses.

Our solution solves the issues of:

  • Only considering channels in isolation, rather than as an ecosystem
  • Lack of cohesive measurement across all touchpoints
  • The limitations of GA4’s data modelling
  • The need for a data science team to process and analyse complex data

Instead, our platform offers a comprehensive view of customer journeys by integrating data from all touchpoints, including online, offline, direct, and indirect channels, using a symbiosis of Multi-Touch Attribution and Econometrics models.

In other words, we handle the complexities of data collection, integration, and analysis, and present you with an accessible and actionable overview of your marketing channels’ performance.

Our reports present figures from all your channels in one place, so you can view your marketing ecosystem from a collaboration viewpoint, not just a siloed one.

Want to understand more about our Omnichannel Marketing Attribution Solution?

Book a call with us — we can talk through your specific needs and how we can help you reform your current attribution model.

Book a Call With Us Today

Unifida x Net Zero Media

Conclusion: Achieving a Unified View of Campaign Performance

The reality is, many businesses are aware that they’re not leveraging the full potential of their attribution insights. The common attribution mistakes we’ve mentioned are just a few, and there are many more that businesses struggle with.

However, with the right tools and strategies in place, it is possible to achieve a unified view of campaign performance. You just need to push past the barriers and take a proactive approach.

Join us in more conversations about marketing attribution over on our blog, or get in touch for advice specific to your organisation.

FAQs

What is the Importance of Attribution in Marketing?

The list is arguably endless, but we’ve narrowed it down to three key reasons:

  1. Improved decision-making: Attribution allows businesses to understand which channels and campaigns are generating the most ROI, leading to informed and data-driven decision-making.
  2. Optimised budget allocation: By understanding which campaigns are driving conversions, businesses can allocate their marketing budget effectively and focus on high-performing channels.
  3. Better understanding of customer behaviour: Attribution helps businesses understand the customer journey and how customers interact with different touchpoints, leading to insights that can improve the overall customer experience.
Why is Attribution Difficult in Multi-Channel Campaigns?

Customers interact with many touchpoints — ads, emails, organic search, offline activity — before converting. Accurately assigning value to each is difficult without integrated data and a model that reflects real behaviour.

Does GDPR Affect Marketing Attribution in the UK?

Yes. GDPR affects how you collect and store user data, including cookie tracking and consent. You must ensure that any attribution setup is compliant with UK data protection laws.

Are There Disadvantages to Attribution in Marketing?

A significant amount of resources is required to implement attribution models, which can be complex, time-consuming, and costly. Additionally, there is the issue of reconciling data from different sources and channels to get an accurate picture of the customer journeys.

Many organisations simply don’t have the tools required, and that’s where vendors like UniFida come in. With an expert team of data scientists and a powerful attribution solution, we can help you overcome these challenges and set up effective attribution for your business.

How to Integrate & Get Value from a Customer Data Platform (CDP)

unifida data platform

While many organisations are aware of them, fewer understand how to integrate a CDP effectively or extract long-term value.

Customer Data Platforms (CDPs) have moved firmly into the spotlight as marketers seek better ways to unify data, personalise campaigns, understand customer behaviour, and deliver measurable results.

The importance of personalisation is nothing new, and a wealth of evidence underpins the business success it can drive.

Research by McKinsey & Company uncovered that “companies that excel at personalization generate 40% more revenue…” Furthermore, 71% of customers now expect to be presented with personalised experiences in their buying journey, and 76% actually become frustrated when they aren’t offered any. [1]

Effective personalisation can only be achieved when one wholly understands their customers and their journeys. A CDP is a fundamental tool in achieving such clarity.

This article is for those in that in-between stage—aware of the possibilities of a CDP, yet unsure how to make them a reality.

We’ll explore what a CDP is, how it adds value, and why the real key to success lies not in the technology alone, but in the organisational alignment that supports it.


What is a CDP?

A CDP consolidates and organises customer data from multiple sources to create a unified view of each individual.

Unlike CRMs (Customer Relationship Management systems) or DMPs (Data Management Platforms), a CDP is designed to ingest data from across online and offline touchpoints—including web, email, social, customer service, and transactions—and make that data available to other systems in real time.

See a Real Example of a CDP in Action


Why are CDPs Important for Businesses?

Why does this matter? Because modern marketing depends on having the right data at your fingertips.

With a CDP, you can stop relying on fragmented systems or guesswork. Instead, you can target individuals with relevant messages, track performance more accurately, and stay compliant with data regulations like GDPR.

data driven marketing


Building a Streamlined & Cohesive Customer Journey

A customer purchase journey that has friction or isn’t cohesive at each step will lead to a negative experience. The customers won’t return and may not recommend the business to others.

But, with the support of a CDP, businesses can better understand their customers’ behaviour, preferences, and needs throughout their journey. This allows for personalised and seamless experiences that can increase customer satisfaction, loyalty, and retention rates.

Learn More About Customer Journey-Based Marketing


More Tactical & Targeted Marketing

Moreover, CDPs can also help businesses with targeted marketing efforts.

By having a centralised database of customer information, businesses can segment their customers based on various characteristics, such as demographics, behaviours, and interests, for more effective and efficient campaigns. They can also use the data in the CDP to build propensity models that predict individual customer behaviour.


More Effective Customer Segmentation

CDPs allow you to build dynamic segments based on a wide range of customer data points. Besides demographic information, you can consider behavioural data, such as purchase history and browsing journeys, as well as Customer Lifetime Value (CLV) to segment your customers.

The more you can narrow down and niche your segments, the more you can tailor your marketing messages and offerings to them. This will lead to higher engagement, conversions, and retention rates because customers feel like you understand their needs and wants.

Read more on this topic: Customer Lifetime Value Demystified: A Guide for Data-Driven Marketers

Unified Customer View

Perhaps the most attractive benefits of a CDP is the ease of accessing all of this rich customer data in one view.

Rather than needing to navigate across and between various data sources (CRM, web analytics, email platforms, POS systems, etc.), a CDP presents you with the metrics that matter most in one easy-to-digest dashboard.

These insights can be shared within the marketing team or presented clearly and informatively to clients, stakeholders, and leadership.

It also aids more efficient and data-driven decision-making by providing near-real-time information and allowing for quick adjustments to campaigns or strategies.

increasing customer loyalty


CDP Use Cases: Unlocking Value Across the Business

Well before CDP integration can begin, you must establish the use cases for such a technology.

A CDP can serve many purposes, but it is crucial to have a specific goal in mind when implementing one.

This conversation needs to happen comprehensively within the organisation—whether in marketing, IT or another department—as a CDP will affect most areas of the business. Processes will likely need to be adapted, team roles might shift, and new technologies may have to be introduced.

Here are a few CDP use case examples:

  1. Single Customer View — Unify online and offline data into one complete profile to enable personalised marketing and smarter decision-making.
  2. Personalised Cross-Channel Campaigns — Use real-time data from the CDP to tailor messages across email, SMS, paid ads, and web experiences based on user behaviour and preferences.
  3. CLV Modelling — Identify high-value customers and their attributes to drive better recruitment strategies.
  4. Journey-Based Trigger Campaigns — Automate communications based on customer lifecycle events, such as first purchase, abandoned basket, inactivity, or birthday, using behaviour-triggered workflows.
  5. Predictive Analytics for Campaign Targeting — Leverage machine learning within the CDP to predict the likelihood of conversion or churn, enabling smarter allocation of budget or campaign effort.
  6. Consent & Preference Management — Track and enforce user consent across all channels and ensure GDPR-compliant data usage in all marketing activities.
  7. Marketing Attribution & ROI Tracking — Tie campaign performance back to actual customer outcomes across channels, enabling true multi-touch attribution.

These use cases extend beyond marketing. Sales teams benefit from deeper customer insights. Customer service can access context for more effective support. Even finance can better understand ROI across campaigns.


Organisational Readiness: What Needs to Change Internally for CDP Implementation

Despite their capabilities, CDPs are not plug-and-play tools. Implementing one successfully means preparing your organisation for change—not just technologically, but operationally and culturally.

To unlock full value, your teams must rethink how campaigns are planned and activated. For example:

  • Marketing will need to move from campaign-based thinking to audience-first planning.
  • Data ownership must be shared across departments, not siloed.
  • Governance frameworks should be adapted to ensure responsible data use.

From the many conversations we have had with prospects and clients about CDP, we often see this kind of organisational change can be quite slow.

Legacy processes, team structures, and internal buy-in often create resistance. That’s why it’s crucial to choose a CDP partner who can help navigate these challenges through consultation and support.

Watch Our Video for Deeper Insights on CDPs


Why Choose UniFida to Help You Get Value from a CDP

UniFida offers more than just a CDP. We provide a full-service solution that includes expert support from day one. Our platform is built with GDPR compliance, marketing activation, and business performance in mind.

We work closely with clients to demystify the CDP journey. We don’t expect you to figure it out alone. Instead, we help you create a plan that makes sense for your organisation and implement it in a way that drives measurable results.

Learn More About Our Insight-Led CDP

screen view of UniFida customer data platform


Conclusion & Next Steps

Integrating a CDP is not just a technical exercise—it’s a strategic transformation. With the right approach and partner, you can turn complex customer data into your most powerful marketing asset.

If you’d like to explore how a CDP could work for your organisation, we’d love to help. Get in touch with the UniFida team for a consultation tailored to your goals.

Book a Call With Us Today


FAQs

What is the Difference Between a CDP & a CRM?

A Customer Data Platform is a type of software platform that collects and organises customer data from various sources to create unified customer profiles.

Often, a CDP will consolidate data from a CRM, along with other sources such as website interactions, social media activity, and purchase history. This data can then be used for marketing and personalisation efforts.

A Customer Relationship Management system is a type of software that manages customer interactions and data throughout the customer lifecycle. This can include sales, customer service, and marketing efforts.

A CRM focuses on managing and using customer data for specific business processes and functions.

Do You Need a CRM If You Have a CDP?

A CRM and CDP work effectively alongside each other, and utilising both is greatly beneficial.

A CDP will provide that single customer view, while a CRM will provide the tools to manage those insights and interactions. They both have their own unique features and capabilities that can greatly enhance your marketing.

What’s Involved in CDP Integration?

A significant organisational shift needs to occur as part of integrating a CDP, as it requires collaboration between multiple departments such as marketing, sales, and IT.

The process involves collecting data from different sources or silos within the organisation and combining them into a single source of truth.

Once the data is collected, it needs to be cleaned and standardised to ensure accuracy and consistency.

A CDP vendor can handle the integration and presentation of data from different sources, making it easier for businesses to use the data effectively.

Who Needs a CDP?

Some examples of industries or organisations that can benefit from a CDP include:

  • Cruise lines
  • Insurance
  • Retail
  • Travel
  • Charities
  • E-commerce

There needs to be a willingness to invest a considerable budget into the implementation and maintenance of a CDP, so typically any businesses with a substantial marketing budget will be able to get the most value out of a CDP.

The Importance of Data-Driven Decision Making in Marketing

data driven marketing

You’ve likely heard the term data-driven decision-making in marketing, but it is far more than just a buzzword.

The industries in which marketers operate today are only becoming more competitive, and remaining stagnant when your competitors are making smarter marketing strategy moves will be detrimental to the growth of your business.

Data-driven decision-making in marketing is a huge topic of conversation, with debates that span across multiple industries.

But one thing that remains constant is that incorporating data into your marketing strategy will lead to more effective and efficient decision-making.

At UniFida, we encourage and support organisations to take more data-driven actions by providing them with the insights to do so.

Our Marketing Attribution Solution helps businesses understand the impact of each marketing touchpoint on their customers’ journeys, allowing them to allocate their resources more informedly and strategically.

We also offer Customer Data Platform services to centralise and unify customer data from various sources, providing a hub where data-driven decision-making can sprout.

Get in touch today to know more about how our services can help your organisation become more data-driven.

Talk To Us Today


What is Data-Driven Decision-Making in Marketing?

Data-driven decision-making in marketing refers to the process of using data and analytics to guide marketing strategies, campaigns, and initiatives.

Rather than just assuming something will work because it has in the past or because it’s common practice, data-driven decision-making involves using actual hard data and insights to inform marketing decisions.

The process is by no means simple.

It involves collecting, analysing, and interpreting data from various sources, such as customer interactions, market trends, and consumer behaviour. This data can come from various sources, including social media, website analytics, surveys, and sales data.

In the context of marketing, this can help shape many marketing choices, such as who to target, what channels to use, when to launch, what messaging resonates, and how to allocate budget.


Examples of Data-Driven Marketing Decision Making

Paid Ads: You notice from the Meta Ads Manager that users aged 25-34 convert best from Instagram Stories. So, you increase your budget for that format and audience.
SEO Strategy: After analysing GSC, you find that a certain blog post drives tons of impressions but low clicks. You update the meta title and description to improve CTR.
Email Marketing: Based on open and click rates, you segment out your most engaged subscribers for early access to a product launch.
Product Decisions: A/B testing landing pages shows that one version consistently outperforms another in sign-ups, so you roll out the better version sitewide.
Cross-Channel Interactions: Marketing attribution uncovers that customers who engage with your social media ads are more likely to purchase through email campaigns.

issues with google analytics 4


5 Key Benefits of Data-Driven Marketing Decisions

To help push businesses in the direction of making data-driven marketing decisions, it can be helpful to visualise the potential benefits that can be gained from implementing such a strategy.

There are plenty of advantages that could be reaped by adopting a data-driven approach, but here are five key benefits that stand out as particularly significant.


Better Customer Journey Personalisation

Delivering a personalised and cohesive customer journey experience can be greatly enhanced through data-driven marketing.

Any customer journey should be frictionless with consistent messaging, particularly when multiple channels are used to engage with customers.

By collating data on customer interactions and behaviour, businesses can better understand how customers navigate through their sales funnels and identify where common obstacles lie.

This allows for targeted improvements to be made to enhance the overall journey experience while also maximising conversions.


Improved ROMI

Marketing budgets are often limited in many organisations, and the budget for your next campaign or financial year can depend on the figures seen in your previous campaigns.

By utilising customer data and implementing targeted strategies, businesses can not only improve their conversion rates but also increase their return on marketing investment (ROMI).

This is achieved by reducing wastage on ineffective strategies and instead focusing on strategies that have proven to generate higher conversions.

A knock-on effect is that it can become easier to communicate this success with your internal stakeholders, such as senior management or investors, and gain their support in future marketing efforts.

Read more on this topic: What is a Good Marketing ROI? & Why It’s Not What You Think

measuring marketing ROMI


Continuous Campaign Optimisation

Campaign optimisations and data-driven decisions are really mutually reinforcing. The more you optimise your campaigns, the richer the data becomes, and the better-informed decisions you can make for future campaigns.

For example…

Say you have recently launched a multi-channel campaign for your new men’s skin cream. You have invested significant resources and budget into this campaign, but after the first week of testing, you notice it is not performing as well as expected.

Rather than scrapping the entire campaign and starting from scratch, you can use the data collected to make informed decisions about optimising and adjusting the campaign for better results.

Your data can allow you to bump up the budget for certain channels that show promising results, while scaling back on others that are not yielding as much success. You might find certain channels work well in tandem, such as social media and email marketing, while others may not have as much impact when used separately.

In addition to using data to improve your current campaign, it can also help guide future campaigns, so it doesn’t just benefit the here and now.

Read more on this topic: How to Measure Marketing Campaign Success Accurately


Reduced Risk Through Evidence-Based Decisions

There is almost always a certain risk involved when it comes to marketing, as there is no guaranteed formula for success. However, by utilising data analysis and making evidence-based decisions, you can somewhat reduce a level of this risk.

When making choices based on data, you are relying on concrete information rather than intuition or assumptions.

It goes without saying that this runs a risk of businesses becoming singularly driven by data, which can have a negative impact on innovation, so there needs to be a balance struck between data analysis and creativity.

Unifida vs GA4


Better Alignment Across Teams

Data analysis can also help with aligning teams by providing a common source of truth.

By utilising data, teams can work together more effectively and efficiently as they are all working towards the same goals and using the same information. This can lead to better collaboration, communication and ultimately a more cohesive team dynamic.


What are the Barriers to Data-Driven Decision-Making in Marketing?

Implementing and shifting your marketing to be more data-driven is a huge task, and it is not something that will happen overnight. There are a number of barriers and challenges that businesses may face when trying to adopt this approach, such as:

  • Lack of data literacy: Not all employees may have the necessary skills or knowledge to understand and interpret data effectively. This can lead to misinterpretation of data, hindering decision-making processes.
  • Resistance to change: Some team members may be resistant to changing their current methods and strategies, especially if they have been successful in the past. This can make it difficult to introduce new data-driven practices.
  • Data quality issues: If the data being analysed is incomplete, inaccurate, or biased, it can lead to faulty insights and decisions. This makes it crucial for organisations to have proper data governance and quality control measures in place.


The Gap Between Data Collection & Interpretation

As a provider of insight-led marketing attribution services, we have spoken to many prospects and clients about the importance of pushing for more data-driven strategies. However, there is a gap between presenting hard data and businesses knowing how to interpret said data (in other words, what to do with it).

The numbers can only take you so far — there must be a human element to make sense of and act on the information.

This involves changing current processes, switching mindsets, and introducing new technologies, which can be uncomfortable for some businesses initially. But there should be confidence in knowing that the end result will be a better understanding of your customers and, ultimately, improved business performance.

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How UniFida Can Support Your Data-Driven Marketing Strategy

To help eliminate some of these barriers to becoming more data-driven, we can provide you with an intelligent marketing attribution solution that provides a holistic view of your customer journeys, channel performance, and campaign success.

When coupled with our CDP, UniFida can also assist in data consolidation, allowing for more accurate and efficient customer data analysis.

The challenges that come with data gathering can be addressed through UniFida’s data aggregation capabilities, ensuring you have access to all relevant customer information in one place.

This includes both online and offline data sources, such as website interactions, purchase history, social media engagement, and more.

You can learn more about our marketing measurement solutions below, or you can book a call with us to discuss how we can tailor our support to you and your organisation.

Learn More About UniFida’s Data-Led Attribution Solution


Conclusion: The Impact of Data-Driven Decision-Making in Marketing

Beyond the difficulties and challenges that come with newly adopting a data-driven approach to marketing, the benefits and potential for growth are undeniable.

With the ability to access vast amounts of data and identify patterns and trends, businesses can make more informed decisions that drive results and improve overall performance.

Not only does this lead to better customer experiences, but it also allows companies to target and engage with their audience in more meaningful ways, positioning them for long-term success.

To read more on data analysis and its impact on business, read our article How the Consequences of Data Misinterpretation Lead to Poor Marketing Decisions.


FAQs

How is Data Used in Marketing Decision-Making?

There are various ways that data is used in marketing decision-making. Some common examples include:

  • Identifying target audience demographics and behaviours
  • Measuring the success of campaigns and initiatives
  • Conducting market research and competitive analysis
  • Personalising marketing efforts through data-driven insights
  • Identifying trends and predicting future consumer behaviour
How Important is Data When Making Marketing Decisions?

It’s a must-have. Data is essential in making informed and strategic decisions in marketing. With the amount of consumer data available, marketers can now understand their target audience more granularly.

How Do You Implement Data-Driven Marketing?

It requires a complete shift within a business, and not just the marketing team. Current processes will need to be assessed and adapted, team roles may need to be reshuffled, and there may be a need to invest in new technology.

Companies must also ensure they are compliant with data privacy laws, such as GDPR, and have processes in place for handling and securing consumer data.

What are the Disadvantages of Data-Driven Decision-Making?

You can have too much of a good thing, and that includes utilising data to make decisions. Here are some potential disadvantages of relying solely on data-driven decision-making:

  • Lack of Context: Data can give you insights into what is happening, but it does not always provide the context behind why it’s happening.
  • Data Bias: Data interpretation can reflect the biases of those collecting and analysing it, which can result in biased decision-making that perpetuates discrimination or inequality. This is why a third-party source with no stake in your business can provide a more neutral perspective.
  • Limited Scope: Data is only as good as what you collect and measure. If important factors are left out or not measured, it can lead to incomplete insights and misguided decisions.

Data and numbers provide a robust foundation for decision-making, but they are only one piece of the puzzle.

How to Measure the Success of Your Marketing Campaign Accurately & Effectively

how to measure the effectiveness of a marketing campaign

As a CMO, marketing manager, or other integral part of the marketing ecosystem, knowing how to measure the success of a marketing campaign is crucial, as you well know. But we also know there are many complexities when it comes to doing this accurately.

Whether tracking offline and online interactions, attributing conversions correctly, or understanding the impact of different channels, measuring the success of your marketing campaigns is no doubt challenging. If you don’t have the right processes in place, that is.

While a digital campaign might show stellar results on the surface, it might not be the full picture. For example, a customer may have seen your social media ad campaign, but then decided to do their own research before making a purchase.

This additional touchpoint may have influenced their decision, but without proper tracking and attribution, it may not be accounted for in your campaign’s success, which can lead to incorrect data and ineffective decision-making for future campaigns.

Our managing director, Jo Young, has recently led some thought-leadership talks on overcoming the difficulties of measuring marketing success, so we thought it would be fitting to share some of our expert insights on our blog, too.

We’ll delve into how to accurately (and effectively) measure the success of a digital marketing campaign, as well as explore the importance of proper tracking and attribution for accurate data analysis.

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How is Marketing Campaign Success Measured?

You’re likely already using a number of metrics to track your marketing efforts, but many of the common KPIs (key performance indicators) often measure only surface-level aspects of a campaign’s success.

While such metrics can provide a general overview of your marketing performance, they do not truly give you a complete picture of the impact your efforts are having on your business.

Common Marketing KPIs & Campaign Success Metrics

  • Website traffic: This metric shows how many people are visiting your website, but it doesn’t reveal how engaged or interested they are in your brand.
  • Click-through rate (CTR): CTR measures the number of clicks on a specific marketing message or call to action, but it doesn’t show whether those clicks lead to conversions or sales.
  • Social media likes and shares: While these metrics can give you an idea of how many people are interacting with your brand on social media, they don’t necessarily equate to business success. Likes and shares may not translate into actual purchases or conversions.
  • Open rates: This metric is commonly used in email marketing and measures the percentage of recipients who open your email. However, it doesn’t necessarily show whether those opens lead to conversions or sales.
  • Impressions: While it’s good to know how many people have seen your content, it doesn’t necessarily mean they have engaged with it or taken any action, which is ultimately what you’re trying to achieve.
  • Conversion rate: This is the percentage of people who take a desired action after engaging with your content, such as making a purchase or filling out a form. It’s generally considered one of the most important metrics to track, as it directly reflects the effectiveness of your marketing efforts.

While these metrics are important, it’s also essential to consider the context in which they are measured. For example, a high click-through rate may not necessarily result in a high conversion rate if the landing page is not optimised for conversions.

These metrics should be balanced with other qualitative KPIs, such as customer retention rate, lifetime value, and customer satisfaction. It’s easy to become number-driven and lose sight of the bigger picture, which is to build a strong and loyal customer base.

We’ll note at this point that we’re not suggesting you shouldn’t be using these metrics—they are important to track and analyse. But there are other factors to consider as well.

best KPIs

How to Measure Marketing Campaign Effectiveness

When attempting to measure and analyse a campaign’s effectiveness, you should also consider numerous other metrics.

While the results generated from the above metrics can be indicative of your success, they don’t give you full transparency. Let’s take a look at some of these other important measurements:

Return on Investment (ROI)

Let us not shy away from the simple fact that, for the most part, the underlying objective of any marketing campaign is to generate a positive return on investment (ROI). In other words, you want to ensure your marketing spend leads to a profitable outcome.

Particularly when communicating with stakeholders or trying to secure a budget for the next financial year, being able to demonstrate a positive ROI is crucial.

ROMI will tell you whether or not your marketing efforts are paying off, and what areas of your campaign may need to be improved in order to generate a higher return.

How to Calculate ROI for a Marketing Campaign

To calculate ROMI, you’ll need to gather data from your marketing campaign, such as the total cost of your marketing activities and the revenue generated from those efforts. Here’s the formula for calculating ROMI:

ROMI = (Revenue – Marketing Cost) / Marketing Cost

ROMI is by no means an easy metric to calculate, as it requires accurate and detailed data.

Learn How to Overcome Challenges of Measuring ROMI

We can support the process of calculating ROMI by implementing effective tracking and analysis methods with UniFida’s Marketing Attribution Solution.

Our solution takes into account all marketing touchpoints and customer behaviour to accurately measure the impact of each marketing channel on overall revenue.

This not only helps in calculating ROMI but also provides valuable insights into which channels are most effective in driving revenue and where to allocate resources for maximum return on investment.

Learn More About Our Attribution Solution

how to increase roi

Customer Loyalty

The primary target of a campaign isn’t always to generate immediate sales, but to build customer loyalty.

Many markets are becoming saturated with similar products or services, making it increasingly difficult to rely on new customer acquisition alone.

A successful marketing campaign should not only focus on attracting new customers but also on retaining existing ones. This can be achieved through various strategies, such as personalised communication, exclusive offers, and excellent customer service.

Customer loyalty is often ignored or forgotten as a measure of success where businesses have a tunnel vision of acquiring new customers. But it’s been found that increasing your customer retention rates by 5% can increase profits by 25%-95%, so solidifying and nurturing a loyal customer base is critical for long-term success.

Customer Lifetime Value

Customer lifetime value (CLV) is a metric that measures the total worth of a customer to a business over the entire duration of their relationship. It takes into consideration the amount of money they spend, how often they make purchases, and the length of their relationship with the company.

We have an entire article explaining CLV and its importance, so we recommend saving this for further reading.

CLV Demystified: A Guide for Data-Driven Marketers

The success of a marketing campaign’s effectiveness can be measured by the CLV of its customers.

A high CLV indicates that a company is retaining loyal and valuable customers, while a low CLV may indicate marketing is not attracting the right target audience or that the customer experience is lacking. In which case, a company may need to reevaluate their marketing strategies and customer satisfaction levels.

But it’s not just about the numbers; understanding CLV can also help businesses build stronger relationships with their customers, leading to increased customer loyalty and retention.

measuring analytics

Cross-Channel Customer Journey Analysis

The success of a marketing campaign can also be broken down by channel to see if there were specific areas that performed better than others. This can be done through cross-channel analysis, which tracks how customers interact with a brand across different channels, like social media, email, and website visits.

Learn More About Cross-Channel Marketing Attribution

While a holistic approach to marketing is important, understanding each channel’s individual impact on customer behaviour can help businesses allocate resources more effectively and tailor their messaging to specific audiences.

Furthermore, cross-channel analysis can uncover any gaps or inconsistencies in the customer journey, allowing companies to make improvements and provide a seamless experience for their customers.

Imagine you work for a brand that designs and sells high-end outdoor gear through your eCommerce website, and you have just launched a new campaign focused on promoting your latest hiking backpack.

You use a combination of marketing channels to reach potential customers, including Meta ads, email campaigns, and influencer partnerships.

You see a spike in website traffic and sales after the campaign launch, which is great news. But you don’t know which of the channels were most effective in driving these results, or if your customers took a specific path to make a purchase.

This is where cross-channel analysis comes in. By looking at the customer journey across all channels, you can see how each contributes to the overall success of your campaign.

Let’s say that when you dive deeper into the data, you notice most sales come from your email campaign and influencer partnerships. Your social media ads, on the other hand, seem to be underperforming, which is the channel you invested most of your budget in.

While the backpack campaign may be a general success, your social media strategy clearly didn’t hit the mark, therefore, you could argue the campaign wasn’t as successful as it could have been.

The Importance of Accurate (& Comprehensive) Campaign Success Measurement

Approaching marketing measurement more holistically (i.e., not limited by vanity metrics like clicks or impressions) is crucial for accurately understanding the impact of your campaigns. While these metrics can be useful for preliminary insights, they do not provide the full picture of campaign success.

Being restricted by limited metrics can result in flawed decision-making and hinder the ability to fully optimise future campaigns.

How Data Misinterpretation Leads to Poor Marketing Decisions

Where you may have initially considered a campaign successful because it generated high sales, further analysis may reveal these sales were not from your target audience, and the cost per acquisition was actually much higher than anticipated, or you actually didn’t generate ROI from the channel you invested the most into.

Alternatively, your campaign might have been hugely successful, and so you’ll want to replicate that in future campaigns by identifying what made it successful and incorporating those elements into your strategy, such as which channels you used, were there any valuable cross-channel interactions, what messages resonated with your audience, and so on.

By having a broader range of metrics, you can better understand the overall impact of your campaign and make more informed decisions for future campaigns.

How UniFida Simplifies Complex Marketing Measurement

At UniFida, it is our goal to simplify the process of tracking and measuring the success of your marketing efforts with our advanced Marketing Attribution Solution.

Combining Multi-Touch Attribution modelling with Econometrics, our customer journey-based approach provides you with a complete analysis of your campaign’s performance, taking into account all touchpoints and channels.

With UniFida, you can easily identify which marketing activities are actually working and which are not, enabling you to make data-driven decisions for your future campaigns.

Our Marketing Attribution Solution also enables you to calculate the ROI of each channel and optimise your budget accordingly.

Our Customer Performance Metrics also provide valuable insights into the effectiveness of your marketing campaigns by tracking metrics such as customer value, acquisition, and retention rates.

Talk to us today about how we can support your business with our intelligent Marketing Attribution Solution and take the guesswork out of measuring your marketing performance.

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analytics in marketing

Key Takeaways: Measuring Marketing Success

It’s a vast and complex topic, with many nuances and debates surrounding it. However, here are some key takeaways to remember when it comes to measuring marketing success:

  • Define clear and specific goals—Before you can measure your success, you need to clearly define what success is for your business. This will help guide your metrics and ensure they align with your overall objectives.
  • Use a variety of metrics—Don’t rely on just one or two metrics to gauge the effectiveness of your marketing efforts. Instead, use a mix of quantitative and qualitative data that can provide a more holistic view of performance.
  • Continuously track and analyse data—Measuring marketing success is an ongoing process. Make sure you regularly track and analyse data to uncover trends, and use this information to make informed decisions about your strategy.
  • Don’t ignore customer performance metrics—While it’s important to track metrics related to your channels and campaigns, don’t forget to also monitor customer performance metrics, as this is really where the success of your overall marketing lies.

And when it comes to attributing success or failure to specific channels and analysing your customer journey, UniFida can help you make sense of all your data.

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FAQs

What is a KPI for Campaign Performance?

This depends on the type of campaign you are running. Some common KPIs for campaign performance include click-through rate, conversion rate, and return on investment.

However, other KPIs may include customer engagement, brand awareness, or lead generation, depending on the goals of your campaign.

How Do You Analyse Digital Marketing Campaigns?

There are several ways to analyse marketing campaigns, including:

  • Tracking and measuring key metrics
  • Conducting A/B testing to compare different campaign elements and determine which performs better
  • Monitoring customer feedback and sentiment to gain insights into how the campaign is perceived by the target audience
  • Utilising data analytics tools to identify trends and patterns in consumer behaviour
  • Conducting surveys or focus groups to gather qualitative data on the effectiveness of the campaign
  • Analysing channel performance to determine which channels are most effective for reaching the target audience
How Would You Evaluate the Success of the Campaign?

The success of a campaign depends on its aim and KPIs. If the goal is to increase brand awareness, measuring an increase in brand mentions and social media engagement would be a good way to evaluate success.

If your main goal is to drive sales or conversions, tracking the number of website visits, click-through rates, and purchases made through the campaign can determine its effectiveness.

Broader success metrics, like ROI and cost per acquisition (CPA), can also be used to measure a campaign’s overall success. These metrics take into account the campaign’s cost and compare it to its results, providing a more comprehensive view of its impact.

How Do You Account for Offline Channels When Measuring Campaign Success?

Econometrics or Media Mix Modelling (MMM) are often used to account for offline channels such as TV, radio, and print in measuring campaign success. These methods use statistical analysis to determine the contribution of each channel to overall campaign results.

UniFida’s Marketing Attribution Solution uses an approach that combines Econometrics with digital attribution, taking into account both online and offline channels and allowing for a more accurate and complete view of the campaign’s impact.

How the Consequences of Data Misinterpretation Lead to Poor Marketing Decisions

Black Box Attribution

In a landscape that’s becoming more and more data-driven by the day, the consequences of misinterpreting data cannot be ignored — and the ‘domino effect’ they have on business decisions can be disastrous.

When we were at school, we were all taught how to do correct maths to ensure that the numbers add up or multiply correctly. What we were not usually taught was that the numbers may have consequences.

In fact, numbers can be bearers of wonderful news, or they can spell disaster, and, in extremist, the end of an enterprise.

With so much customer data at our fingertips, it’s easy to make the mistake of relying solely on numbers and not considering the context behind them. When presented with business numbers — and assuming the maths are correct — there are two key questions to ask;

  • Are they answering the right questions?

And, if they are,

  • What is their impact on our decision-making going to be?

To help you (and your team) make consistently good decisions based on data-driven marketing, it’s worth investing some time in understanding the consequences of misinterpreting data, and that’s where this article comes in.

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What is Data Misinterpretation in Marketing?

When we look at data misinterpretation in marketing, we’re talking about the incorrect translation of data and its subsequent misuse in making decisions in the marketing strategy.

Data misinterpretation can happen at any stage of the data analysis process, from collecting and cleaning data to interpreting and communicating insights. This means that even if you have a solid data collection process in place, incorrect interpretation of the data can still lead to poor marketing decisions.

Some common mistakes in interpreting business data include:

  • Data sampling: Analysing too small a sample of data can lead to incorrect assumptions and decisions.
  • Confirmation bias: Interpreting data based on preconceived notions or beliefs rather than objectively analysing it.
  • Lack of context: Not considering external factors or the bigger picture when interpreting data can lead to incorrect conclusions.
  • Siloed data: Not integrating data from several sources can lead to a narrow and biased view of the data.
  • Incorrect marketing attribution models: Using incorrect attribution models can skew data and lead to inaccurate interpretations.

The scary thing is that it’s quite easy to commit these mistakes without even realising it, and the consequences can be dire.

Trusting your data with reliable experts is one way to avoid data misinterpretation, but it’s important for businesses to also have a solid understanding of business metrics and how they relate to their specific business goals.

Talk to Our Data Experts Today

It’s also important to note the difference between data misinterpretation and misrepresentation.

While data misinterpretation refers to incorrect assumptions made when analysing data, data misrepresentation is the deliberate manipulation of data for personal gain, like falsifying sales figures or inflating website traffic numbers. Both can lead to poor marketing decisions but require different solutions.

marketing ROI

The Domino Effect – Examples of How Data Misinterpretation Can Lead to Marketing Failure

One can almost envision the consequences of data misinterpretation as falling dominos. When one decision is based on incorrect data interpretation, it can affect multiple areas of the business and lead to a snowball effect of poor marketing decisions.

Let’s set the scene with an example:

A business has been tracking its website traffic and sees a significant spike in visits from a particular location. Based on this data, they decided to launch a targeted ad campaign in that specific location, hoping to reach and convert more potential customers.

However, what they didn’t consider was that the spike in website traffic was due to a music festival in that location, resulting in inflated numbers.

As a result, the subsequent ad campaign targeting that location is unsuccessful and doesn’t bring in any new customers. The business then decides to increase its marketing budget to compensate for the lack of results, leading to an overall decrease in profitability.

This is just one example of how data misinterpretation can have a domino effect and ultimately lead to marketing failure. The data may have been accurate, but the lack of context and correct interpretation led to poor decision-making and, in the end, a poor ROMI (Return on Marketing Investment).

Another example, of less significance but nevertheless important, is when marketers justify their investments in marketing with the wrong business KPIs; they will count clicks, impressions, and opens rather than changes to brand recognition, customer recruitment, and actual sales.

Readers of the economist Dieter Helm will recall how he lays into the way our national accounts are presented in his book ‘Legacy’.

His point is that they focus on GDP and the extent of Government borrowing rather than on the extent to which we are improving or degrading our natural and man-made infrastructure. By not answering the right questions, they allow us to ignore the consequences, and hence the terrible decline in our man-made and natural ecosystems over the last few decades.

overcome difficulty of ROMI

The Consequences of Data Misinterpretation for Marketing Teams

  • Wasted time and resources: Making decisions based on incorrect data can lead to wasted time, money and misallocation of resources.
  • Reputation damage: Incorrect data can result in poor marketing decisions that can damage a company’s reputation and brand image.
  • Loss of competitive edge: Misinterpreting data can lead to incorrect assumptions about the market, causing businesses to lose their competitive edge.
  • Missed opportunities: When decisions are based on inaccurate data, it can lead to missed opportunities for growth and success.
  • A negative ROMI: Poor marketing decisions based on data misinterpretation can result in a negative Return on Marketing Investment.
  • Misaligned marketing strategies: Data misinterpretation can lead to incorrect assumptions about customer behaviour and preferences, resulting in a misaligned marketing strategy.

How to Prevent Data Misinterpretation When Developing Your Marketing Strategy

So what it all really boils down to is: how do you avoid making such a costly error?

Here are some actionable steps businesses can take to prevent data misinterpretation in their marketing strategy:

Implement Best Practices for Data Collection & Analysis

Whether you’re collecting data from your latest marketing campaign or tracking customer behaviour on your website, it’s crucial to follow best practices for data collection and analysis. This includes:

  • Clearly defining what data you want to collect and why.
  • Ensuring the data is collected accurately and consistently.
  • Cleaning and organising the data before analysis.
  • Using appropriate statistical methods for analysis.

The larger the business, the more important it is to have a dedicated team or experts responsible for data collection and analysis. Particularly when tracking customer journeys and interactions across multiple touchpoints, it’s important to have a comprehensive understanding of how the data is collected and analysed — or at least put someone in charge who does.

The team at UniFida consists of data scientists and marketing analysts who have a deep understanding of data collection and analysis best practices.

With over 25 years of experience, we’ve refined, tested, and proven these practices to ensure accurate data interpretation and marketing attribution.

Learn More About Our Data-Driven Attribution Solution

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Collaboration Between Data & Marketing Teams

If one of the most common causes of data misinterpretation is lack of context, then one of the best ways to prevent it is through collaboration between data and marketing teams.

Data scientists and analysts may have a deep understanding of data, but they may not possess the same level of market knowledge as marketers and hence spend time answering the wrong questions. On the other hand, marketers may not fully understand how to interpret or analyse data accurately.

Collaboration between these two teams can help bridge this gap and ensure that both sides are on the same page regarding data interpretation and decision-making.

Regular communication, joint meetings, and collaborative projects can lead to a better understanding of data and its implications for marketing strategies.

Invest in Data Analytics Tools & Training

Investing in quality data analytics tools and providing training for employees on how to use them effectively is another crucial step in preventing data misinterpretation.

The analytics tools we use on a daily basis are just that — tools. Without the proper knowledge and training, they can easily be misused or misunderstood, leading to incorrect data interpretation.

Businesses should invest in tools that are user-friendly, intuitive, and provide actionable insights that are easy to understand. Additionally, providing employees with the necessary training on how to use these tools and interpret the data accurately is key to making informed marketing decisions.

Our Customer Data Platform (CPD) is an example of such a tool. With it providing the marketing metrics that you actually need to know, you’ll have the insights and data interpretation necessary for successful strategies.

Metrics like Customer Lifetime Value and Campaign Performance can be viewed and understood by your entire team, making collaboration and decision-making more effective.

Discover More About Our CPD & Attribution Today

deciphering data

The Role (& Risks) of AI in Business Analytics

Artificial Intelligence and Machine Learning (ML) are revolutionising the way businesses collect, analyse, and interpret data. However, with such advanced technology comes risks that businesses need to be aware of:

  • Bias in algorithms: AI is only as unbiased as the data it’s trained on. If the data used to train an algorithm is biased, it will continue to perpetuate that bias.
  • Lack of transparency: AI or ML algorithms can be complex and difficult for humans to understand. This lack of transparency can make it challenging to identify errors or biases.
  • Data privacy concerns: With increased data collection comes higher risks of data breaches and privacy violations.

To mitigate these risks, businesses should ensure that AI algorithms are regularly audited and tested for biases. Additionally, data privacy and security measures should be a top priority when implementing AI technology.

Human oversight should not be overlooked either — having humans involved in the data analysis and interpretation process can help catch any errors or biases that AI may have missed.

Never leave the interpretation of important data solely in the hands of AI. It should be used as a tool to aid decision-making, not replace human intelligence entirely. After all, you know your customers and business best.

A Message for AI Enthusiasts — Numbers Have Consequences!

Avoiding data misinterpretation and preventing the risks associated with AI in business analytics starts with acknowledging the power and impact of data. As AI enthusiasts, it’s essential to understand the consequences of inaccurately interpreting data and the potential risks of relying solely on AI for decision-making.

Through collaboration, best practices, and a human-first approach to data interpretation, businesses can utilise AI technology effectively while minimising the risks.

So, let’s continue to push the boundaries of what AI and data analytics can do for businesses, but always with a critical eye and a human touch.

If you want to leave your data to the experts, contact UniFida today to learn more about how our team can help your business make informed and data-driven marketing decisions.

Talk to Our Team of Data Experts & Analysts Today


FAQs

What is ‘Analysis Paralysis’?

Analysis paralysis specifically refers to the state of over-analysing a situation, leading to decision-making paralysis caused by too much information.

Many of us will have been in a meeting when someone complains of ‘analysis paralysis’; their objection is essentially that too many numbers are having a negative impact on their ability to work out what they really need to know, and what actions should be taken as a result.

What are the Consequences of Wrong Data Entry?

Incorrect data entry can have severe consequences for businesses. It can lead to incorrect decision-making, wasted resources and time, and potentially damage to a company’s reputation.

What are the Most Common Mistakes Made When Analysing Data?

The most common mistakes made when analysing data include:

  • Lack of context and understanding of what the data represents
  • Confirmation bias (only looking for information that confirms pre-existing beliefs)
  • Overlooking outliers or insufficient sample sizes
  • Misinterpreting correlations as causations
  • Answering the wrong questions

It’s crucial to be aware of these potential mistakes and actively work to prevent them when analysing data. Collaboration, quality tools, and a human-first approach can help minimise errors and improve data interpretation accuracy.

Customer Lifetime Value Demystified: A Guide for Data-Driven Marketers

happy customers

Rather than viewing a customer from a single transactional perspective, customer lifetime value (CLV) allows businesses to understand the long-term value of their customer relationships.

From the initial interaction to the final purchase and beyond, CLV enables marketers to make informed decisions that drive customer retention and increase profitability. And measuring CLV has never been more important.

The shift from transactional marketing to relationship marketing has made CLV a vital metric for long-term success.

As personalisation, customer retention, and data analytics become more sophisticated, marketers must leverage CLV to inform decision-making, optimise marketing spend, and foster sustainable growth.

Otherwise, they risk wasting resources on customers who generate little long-term value and miss opportunities to nurture valuable relationships.

This guide will explore how data plays a pivotal role in understanding and optimising CLV.

What is Customer Lifetime Value?

CLV is the total revenue a customer will generate for your business over their entire relationship with you.

Unlike other metrics focusing on individual transactions, CLV considers the entire customer journey and the value they bring to your business over time.

For example, a customer may make a single high-value purchase but never return. While they may contribute a large sum to your revenue, their CLV would be low. On the other hand, a customer who makes multiple smaller purchases over several years would have a higher CLV.

In simple terms, CLV is the total profit you can expect from a customer.

How to Calculate Customer Lifetime Value

The general Customer Lifetime Value formula is as follows:

CLV = (Average Purchase Value x Number of Repeat Purchases) x Average Customer Lifespan

Customer lifetime value

The Role of Data in Understanding & Optimising CLV

To fully grasp the power of CLV, businesses need to move beyond basic calculations and embrace a data-centric approach.

Customer Lifetime Value analysis isn’t just about knowing how much a customer is worth; it’s about understanding why certain customers are more valuable and how to attract and retain them.

Customer Lifetime Value Example

Our research at UniFida has uncovered significant variations in CLV based on acquisition sources across industries as varied as life insurance, hobbies, and wine retailing.

The chart below is a typical example of the decline in customer value over time, with customers in their fourth year from recruitment contributing around 15-20% of what they did in their first year.

When the pathway to a customer’s first purchase is simple, customers can be labelled by a single recruitment source, and the analysis of their LTV by source is straightforward.

But, the acquisition journey is rarely linear. What we usually find is it involves several steps, and so, a particular individual may have been recruited from multiple sources.

For instance, in a case study, we found that customers recruited (or acquired) via social media channels often have a considerably lower long-term value compared to those acquired through direct mail.

Here, only 14% of customers touch a single channel before making their first purchase. This multi-channel engagement complicates customer lifetime value models, making it essential to track and label customers accurately to understand their full value.

How CLV Helps Create Targeted Customer Acquisition Campaigns

Effective segmentation is key to maximising CLV.

By categorising customers based on their lifetime value, businesses can tailor their marketing strategies to different audience segments, ensuring resources are allocated efficiently. You wouldn’t want to spend the same amount on acquiring a customer who spends £10 versus one who spends £10,000 over their lifetime.

Businesses can segment customers based on CLV in various ways, such as:

  • Recency, Frequency, Monetary (RFM) segmentation: grouping customers based on their purchase recency, frequency, and monetary value.
  • Demographic segmentation: targeting customers based on demographic data, such as age, gender, income level etc.
  • Behavioural segmentation: dividing customers based on their purchasing behaviour and preferences.

Once businesses have identified high-value customer segments, they can tailor their marketing to these customers, providing personalised offers and targeted campaigns to maintain their loyalty. Focusing on high-value customers can also reduce customer acquisition costs.

What is eCommerce Personalisation?

Using Customer Lifetime Value Metrics to Inform Marketing Spend

By analysing customer lifetime value, businesses can identify the most effective acquisition channels and optimise their marketing spend and investments to maximise long-term profitability.

Moreover, by monitoring CLV over time, businesses can track the success of their marketing strategies and make adjustments accordingly. For instance, if a certain channel’s CLV decreases over time, it may indicate a need to reallocate resources towards more profitable channels.

Read More About Our Customer Performance Metrics

Predictive Analytics & AI in Forecasting CLTV

As marketing becomes increasingly data-driven, predictive analytics are revolutionising how businesses forecast customer value. These technologies enable marketers to anticipate customer behaviour, identify high-value prospects, and optimise strategies in near real-time.

Benefits of Predictive Analytics in CLV:

  • Forecast Future Value: Predict which customers are likely to generate the most revenue over time.
  • Identify At-Risk Customers: Use behavioural data to spot signs of increasing churn rate and implement retention strategies.
  • Personalise Marketing Efforts: Tailor campaigns based on predictive insights to maximise engagement and conversions, leading to better brand loyalty and customer satisfaction.

AI or ML-driven models can analyse vast amounts of data to provide accurate customer lifetime value forecasts. For example, machine learning algorithms can identify patterns in customer behaviour, such as purchase frequency and engagement levels, to predict future value.

UniFida’s Marketing Attribution Solution uses machine learning algorithms developed in-house to provide accurate and actionable insights into where customers are coming from.

You can filter your attribution reports by your own customer segments, so you can understand what high-value customers are more likely to engage with.

This data feeds into our Customer Performance Metrics Platform, which enables businesses to segment customers based on their lifetime value and track changes over time. This information helps inform targeted campaigns, making the most of high-value customer segments.

Contact Us to See How We Can Help You

increasing conversion rate

Conclusion: Turning CLV Insights into Action

Customer Lifetime Value is more than just a number — it’s a powerful lens through which businesses can view and optimise their marketing strategies. By leveraging data, predictive analytics, and acquisition insights, companies can identify high-value customers, allocate resources effectively, and drive long-term growth.

At UniFida, we specialise in helping businesses unlock the full potential of their data to maximise CLV.

Whether you’re looking to refine your marketing strategies, optimise budget allocation, or harness the power of predictive analytics, our solutions are designed to deliver actionable insights and measurable results.

Ready to take your CLV strategy to the next level? Contact us today to learn how we can help you turn data into growth.

Get in Touch Today!


FAQs

Why is Customer Lifetime Value Important for Businesses?

Customer Lifetime Value is important because…

  • It helps businesses understand the long-term value of their customers and tailor marketing strategies towards high-value segments.
  • It can inform resource allocation and budget decisions, leading to more efficient marketing spend.
  • By tracking CLV over time, businesses can monitor the success of their marketing strategies and make adjustments to maximise profitability.
Should CLV Be High or Low?

Customer LTV varies across industries and businesses. Generally, a higher CLV is preferable as it indicates greater profitability and customer loyalty. However, it’s essential to consider industry benchmarks and the cost of acquiring and retaining customers when evaluating CLV.

How Do You Increase Customer Lifetime Value?

Some strategies for increasing Customer Lifetime Value include:

  • Focusing on customer retention through personalised marketing and exceptional customer service.
  • Upselling and cross-selling products or services to existing customers.
  • Identifying and targeting high-value customer segments with tailored campaigns.
  • Utilising predictive analytics to identify potential high-value customers and proactively engage them.
How Do You Predict Customer Lifetime Value?

Predicting Customer Lifetime Value involves analysing historical customer data to forecast future value. This can be done using predictive analytics and ML-powered algorithms, which identify patterns in customer behaviour and segment customers based on their likelihood of generating high or low-value over time.

Our Customer Performance solution features a Customer Value Tracker, which allows you to see the acquisition contributions from current and previous years’ customers and project these into the future to calculate a forecast of their lifetime value.

Jo Young to Speak on Attribution Modelling at DMA Event

We’re excited to announce that our Managing Director, Jo Young, will speak at the upcoming DMA event, Marketing Measurement: Your 2025 Guide Unwrapped, on the 12th of February 2025.

The event will take place in London and bring together leading industry professionals to discuss the latest in marketing measurement and data-driven strategies.

What We’ll Be Covering

Attribution Modelling —we’ll be discussing practical attribution modelling techniques to optimise marketing spend, improve customer journey insights, and maximise ROI in today’s dynamic digital landscape.

The Event

DMA’s Marketing Measurement: Your 2025 Guide Unwrapped

When?

Wednesday 12th February 2025 @ 9 am – 11 am

Where?

The Goldsmiths’ Centre, London, EC1M 5AD

Deep Dive into Attribution Modelling

Jo will be delivering an insightful talk on Attribution Modelling, sharing her expertise on how businesses can better understand the customer journey and optimise marketing spend. With the ever-evolving digital landscape, accurately attributing value to each touchpoint is critical for making informed decisions and maximising ROI.

Why This Matters to You

UniFida has long championed the power of data in shaping effective marketing strategies, and Jo’s session will highlight practical approaches to attribution that can be implemented across different channels.

Whether you’re grappling with multi-touch attribution complexities or looking for new ways to demonstrate marketing effectiveness to stakeholders, this session promises to offer valuable takeaways.

Stay Connected

Stay tuned to our LinkedIn for post-event updates and highlights from Jo’s session. Downloadable assets and slides will be available after the talk.

Mail [email protected] if you would like to be sent them.

Connect With Jo Young on LinkedIn

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How Accurate is Last Click Marketing Attribution?

attribution report

The term ‘last click attribution’ describes a customer journey measurement system that assumes only the final action before a purchase contributed to a sale and deliberately ignores all the previous steps and influences that might have preceded it.

In around 15% of all online sales, there is only a single step in the customer journey. In these cases, the single click clearly affected the sale.

However, our research has found that 85% of customer journeys involve multiple channels and take place over longer periods. So, where should the credit lie, and why should it be the final touch point, as a last-touch attribution model would assume?

How Accurate is Last Click Marketing Attribution?

Another reason why last click attribution is misleading is that it ignores all the indirect channels that may have influenced the sale, such as TV or Press. That also includes any marketing activity concerned with brand development and not aimed at a short-term response.

However, as many marketers persist with using last click, we decided to undertake some analysis to find out just how misleading it was (and what a better alternative model is).

How Does Last Click Attribution Work?

The last click attribution model simply assigns 100% of the credit for a sale to the final touch point. In this way, the last channel through which a customer comes into contact with your brand is given all the credit for driving that sale.

This model works on the assumption that customers are most likely to convert when exposed to a particular marketing channel or tactic immediately before making a purchase. So, if a search ad or an email was clicked on and then led directly to a purchase, it would receive all the credit for that sale.

We’ve already alluded to the fact that customer journeys are more complex than this simple attribution model suggests, and frankly, last touch attribution doesn’t accurately reflect the reality of how customers interact with brands and make purchasing decisions.

Pros & Cons of Last Touch Attribution

Pros Cons
Requires minimal setup and data analysis compared to more complex attribution models. Fails to account for the multiple touch points (e.g., discovery, consideration) that influence a consumer’s decision before the final click.
Doesn’t require advanced tools or complex tracking infrastructure, making it a cost-effective choice for small businesses. Neglects the role of upper-funnel activities like social media engagement or awareness-building ads.
Integrated into many analytics tools (e.g., Google Analytics), making it easy to apply universally across marketing efforts. Can result in overinvestment in channels driving last clicks and underinvestment in channels that contribute to the awareness or consideration stages.
Useful for campaigns where the goal is immediate conversions, such as flash sales or retargeting efforts. Wrongly encourages a transactional approach to marketing rather than building long-term brand equity through a holistic strategy.

Read more: Is There a GA4 Alternative? Yes, & It’s Here

How Effective is the Last Click Attribution Model?

To prove just how misleading last click attribution is, we’ve done some of our own investigating.

We took data from a large UK retailer who uses a wide range of direct marketing channels and examined all their customer journeys that led to sales in a three-month period.

Here’s how we carried out our research and what we found…

Phase 1 – Weighting the Customer Journey Using Machine Learning

The process we used to compare to last click attribution was to apply a weighting to every step in a customer journey based on machine learning (ML).

The ML approach looks at a number of factors describing each journey step, and the principal ones are to do with intervals before and after each step.

So, for example, if a customer is sent an email, opens it, but then does nothing about it for a week before visiting the client’s website, that email will be given a much lower weighting than if the customer had clicked through from the email to the website soon after they received it.

Using this approach, we can give a comparative weighting to every step in every journey.

In the case of this retailer, there were around 1m journeys in the quarter we examined to track and weight.

Here is an example of the weighting being applied to each step in a customer journey.

Weighting the Customer Journey

In fact, our algorithms have gone one step further and worked out the contribution made by each step in initialising, holding, or closing a sale.

So, here, direct mail gets most of the initialising score, and email has the biggest share of the closing score. But each step gets some share of the sale, as you will see from the column on the far right of the table.

Phase 2 – Comparing Values Attributed By Last Click vs Machine Learning

Now, we move on to comparing the last-click approach with machine learning that looks at all steps in the journey before a sale. You will see that very substantial differences emerge.

The table below shows the comparison between the value given to channels using last click, and the value attributed by our machine learning.

Comparing Values Attributed By Last Click vs Machine Learning

Last Click vs Machine Learning

The differences are considerable. For instance, last click over-values PPC by 22% or, in this case, £1.1m, and under-values direct mail by 13% or £5.1m.

Phase 3 – The Verdict

So, in conclusion, last click is quite simply an extremely inaccurate way to attribute value to marketing campaigns and can lead to a serious misallocation of resources.

It should be avoided at all costs, otherwise marketers risk making decisions based on misleading data. Over- or under-investing in certain channels because last click attribution tells you to do so can ultimately harm your overall marketing efforts and results.

What Model is Better Than Last Click Attribution?

An approach looking at every journey step, and weighting them according to their role, is going to give a much more balanced result, and lead to a more optimised allocation of marketing media spend.

A multi-touch attribution model supported by machine learning is a markedly better alternative to last click attribution. It takes into account all touch points in the customer journey and assigns appropriate weights based on their contribution to driving conversions.

Furthermore, considering the entire customer journey gives a more holistic understanding of the effectiveness of marketing efforts and allows for better decision-making when it comes to budget allocation and campaign optimisation.

Marketing mixes shouldn’t be looked at on a granular, channel-isolated basis, but rather as a collective effort that works together to drive results.

increasing customer loyalty

How to Get Started With Multi-Touch Marketing Attribution

Multi-touch attribution can be a tricky nut to crack, which is why partnering with an attribution vendor who offers this solution is your ticket to success.

At UniFida, we help businesses accurately measure the effectiveness of their marketing channels and campaigns through our advanced attribution model – which takes into consideration all touch points and weights them accordingly.

We use our in-house machine learning algorithms to analyse each customer journey and assign appropriate values to each step, always trained on our client’s own data, rather than any generic model.

With our solution, you’ll have access to a full analysis of your customer journeys and the contribution made by each event, empowering you to make data-driven decisions for your future marketing efforts.

Ready to get started? Use the button below to send us an email or give us a call.

Contact Us Today!

Conclusion: Just How Wrong is Last Click Attribution?

The bottom line is last click attribution is flawed and leads to inaccurate measurement of marketing efforts. It’s time for businesses to move on from this outdated model which risks hindering their marketing performance and results.

Leave behind the misconceptions and embrace a more advanced, holistic approach to attribution that considers all touch points and values them accordingly.

FAQs

What Attribution Model Does Google Use?

Google uses last click attribution as its default model in Google Analytics, which is why we recommend avoiding it for your attribution needs. An alternative to GA4, like our solution, is much more effective.

What is the Most Common Attribution Model?

Last click is one of the most common attribution models used in tracking conversions (despite its flaws). Other popular models include first click, linear, and time decay.

What is the Bias of Last Click Attribution?

Last click attribution is biased towards the last touch point a customer interacted with before converting. This means that any previous events that may have contributed to the conversion are undervalued or ignored, not at all painting a full picture of the customer journey.

What is an Example of Last Touch Attribution?

An example of last touch attribution is when a customer clicks on an ad, then later makes a purchase directly from the website. In this case, all credit for the sale goes to the ad click, ignoring any other touch points that may have influenced the customer’s decision to make a purchase.

What is the Difference Between First Click vs Last Click Attribution?

First click attribution gives all credit for a conversion to the first touch point a customer interacts with, while last click attribution gives all credit to the last touch point.

Both are single-click attribution models, which are greatly limited by their own design as they dismiss the impact of any other events throughout the customer journey.

UniFida Wins Silver at the DMA Awards 2024! Recognising Excellence in Door Drop Campaigns

DMA silver award 2024

We are thrilled to announce that we were awarded Silver at the prestigious DMA Awards 2024 in the Unaddressed Print and Door Drops category.

This award recognises our contribution to an outstanding campaign for Majestic, designed to defy market trends and deliver exceptional results during the critical Christmas trading period.

Titled “Door Drop Delivers Majestic Performance”, the campaign was a collaborative effort that combined data-driven targeting, creative storytelling, and precise attribution to achieve remarkable success.

Despite significant challenges, the campaign’s results speak volumes about the effectiveness of integrated strategies.

See Us Among the Full List of Winning Work for 2024

Tackling Market Challenges Head-On

The retail wine sector faced a tough environment leading into Christmas 2023, with sales across the industry down by 9% YOY (year-on-year). In this context, Majestic set ambitious objectives for the campaign:

  1. Grow sales to exceed 2022 levels and outperform the market.
  2. Re-engage lapsed customers while attracting new ones through targeted door drops.
  3. Drive retail traffic to stores.
  4. Accurately measure the performance of every channel in the media mix.

With just 50% of the previous year’s budget, the challenge was clear: every channel had to deliver a significant impact to meet these goals.

Data at the Heart of the Strategy

At UniFida, we believe in the power of data to drive results. For this campaign, we worked with partners to deliver precise targeting and actionable insights.

The Majestic customer database was segmented using recency, frequency, and value (RFV) data, enriched with Mosaic audience segmentation. These insights were then mapped using Whistl’s Zebra mapping tool, identifying the most valuable postal sectors around store catchment areas.

This data-driven approach ensured the door drops reached households most likely to respond – new customers and those who had lapsed.

By focusing on high-value customer profiles, we were able to optimise offline targeting and create a strong foundation for success.

A Collaborative Effort

The success of this campaign was a testament to the power of collaboration. Key contributors included:

  • Majestic, who provided clear objectives and valuable customer insights.
  • Whistl Doordrop Media, who managed the delivery of unaddressed print materials.
  • Powerhouse Studios, who crafted the creative assets.
  • &You London, who contributed expertise in data and media targeting.
  • UniFida, who ensured precise tracking and attribution.

Together, we developed a unified strategy that integrated multiple channels, including TV, out-of-home (OOH) advertising, digital, and social media, with the door drops forming a cornerstone of the campaign.

Creative That Captivated Audiences

Creativity was critical to the campaign’s success.

The messaging centred on the theme “There’s a Story Behind Every Glass”, celebrating Majestic’s staff’s wine knowledge and expertise. This narrative positioned Majestic as the go-to retailer for fine wines during the festive season.

The door drops featured:

  • A compelling promotional offer of 25% off fine wines.
  • A QR code directing recipients to Majestic’s French Wine Collection online.
  • Clear, localised information, including store addresses, phone numbers, and opening hours.

This creative approach was designed to inspire confidence in Majestic’s brand while providing recipients with clear calls to action, whether to visit a store or shop online.

Delivering Outstanding Results

The results of the campaign highlight the power of combining data-driven insights with creative execution:

  • Sales uplift: Door drop areas experienced a 33% sales increase during the campaign, compared to a 15% uplift in control areas without door drops.
  • Sustained impact: Even two weeks after the campaign ended, door drop areas maintained a 27% uplift in sales, demonstrating the long-tail effect of the channel.
  • Exceptional ROMI: The door drops delivered a return on marketing investment (ROMI) of 48.7:1, the highest of any channel in the campaign.

These achievements were instrumental in helping Majestic report their best-ever Christmas in January 2024, with an 8.1% sales increase despite the challenging market conditions and a significantly reduced budget.

Why This Recognition Matters

Winning Silver at the DMA Awards 2024 is a proud moment for all of us here at UniFida. The DMA Awards celebrate innovation, creativity, and effectiveness in marketing, and this accolade affirms our commitment to delivering impactful results for our clients.

The success of the “Door Drop Delivers Majestic Performance” campaign also underscores the value of unaddressed print as a channel. When executed with precision, it can drive immediate results while delivering sustained benefits, as this campaign clearly demonstrated.

A Heartfelt Thank You to the Team

This achievement would not have been possible without the incredible teamwork and expertise of everyone involved. We would like to extend our gratitude to:

  • Majestic for their partnership and strategic vision.
  • Whistl for their leadership in managing the door drop campaign.
  • Powerhouse for their creative contributions.
  • &You London for their support in data and media targeting.
  • Our own team at UniFida, who provided the tracking and attribution insights that ensured every channel’s performance was measured accurately.

This recognition belongs to all of you.

Let’s Create Something Extraordinary Together

At UniFida, we specialise in turning data into actionable strategies that drive measurable success. Whether you’re looking to optimise your marketing mix or explore the potential of unaddressed print, we’d love to help you achieve your goals.

Get in touch with us today to learn more about how we can deliver award-winning results for your business.

Contact Us Today!