Forrester says that analytics is a top marketing priority!

Forrester has based this claim, that analytics is a top marketing priority, on a survey of 750 analytics decision-makers in larger companies employing more than 500 people (‘The Future of Analytics’, Forrester, July 2020).

To quote from the report: Analytics is a top marketing priority. Of the ten marketing priorities we surveyed, marketers ranked improving their use of data and analytics as a top priority over the next twelve months. More than six in 10 marketers (63%) indicated that analytics was in their top five priorities. In separate research, Forrester found that improved analytics drives business results. In that, connecting customer data across formerly siloed product lines and connecting customer and behavioural data across channels can inform digital improvements that increase sales.

challenges faced when it comes to digital analytics
Challenges organisations face when it comes to digital analytics.

Forrester then went on to ask about what was inhibiting companies from delivering analytics with the following results:

With this in mind we want to explain what we are doing to help marketers using our UniFida technology get the analytics they need.

First, we have removed the problem of siloed data. UniFida’s cloud-based customer data platform technology ingests data from people browsing wherever we can match it to customers, as well as from ecommerce, customer order systems, email service providers, call centres, and where available retail. It then uses all available personal identifiers to build the single customer view. We end up with a ‘single silo’ of all customer data being made available for analysis.

Next, we have integrated with Microsoft Power BI so that data manipulation and visualisation can be undertaken. Power BI allows you to create virtually any report you want and publish it within your organisation. Inside UniFida, Power BI can use all the online and offline data available in the single customer view to tell you how your customers are performing and what they are responding to.

Then to help automate reporting we have built into UniFida a suite of standardised marketing metrics. At the click of a few buttons this will tell you all you need to know about customer acquisition, customer retention, and customer value. It can also tell you how your marketing campaigns are performing, and help you compare test results. All this updated every time UniFida receives new data.

Finally, we have just released our innovative solution to marketing mix modelling. We call it ADEE or algorithmic direct event evaluation. By looking at all the online and offline events that occur in the 90 days before a sale, and using our proprietary AI to weight them, we can tell you what are the drivers behind every order. When summed up this tells you precisely the contribution made by each direct marketing channel you are using from Google PPC to catalogues or email.

We are not trying to say the UniFida has an automated answer to every analytics question you can throw at us, but we expect that it will definitely cover the majority of them. And for those that it cannot solve we have our in-house data science team who can for instance build you a customer segmentation, or a propensity model to predict which of your dormant customers are most likely to be reactivated.

Forrester says that analytics is a top marketing priority. Many of the team who developed the UniFida technology have come from a marketing data science background, so every decision we have made when designing the tool has incorporated the need for marketing analytics.

So, let us know if you would like a quick demo of what UniFida can deliver, as we would be delighted to show you it in action.

 

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

Are you in the dark about your omnichannel performance?

attribution share to measure omnichannel performance
Chart showing the attribution share in an omnichannel environment

Marketing mix attribution is often one of the biggest problems a marketer can face when trying to measure omnichannel performance. How to fathom out in an omnichannel environment how much each channel is really contributing?

And how much for instance are they contributing to new customer recruitment v. existing customer sales?

Google has a solution for attributing what goes on in the digital space, but this leaves out important areas like emails opened, catalogues received, SMS messages, outbound calling, even retail visits.

So, we set about developing ADEE, or Algorithmic Direct Event Attribution.

For us it’s the culmination of a journey which we began by solving the problem of attributing orders to events, where clients were using both online and offline channels.

Curiously, nobody else appeared to be doing this.

We needed to create a result that made sense of the relative contributions of all the online and offline events that took place before each order is placed. (By the way the average is around five per order).

We needed to apply a fair weighting to these events that described the influence they had on each eventual order.

Then we had to add up all the events to the channels in which they took place to understand the value contributed by each channel.

Finally, we needed to let our clients decide whether they wanted to look at all customer orders, or for instance just new customers, or customers buying a particular product category.

I am delighted to say that we ended up creating ADEE!

If you would like me to send you our white paper on ADEE then please email us on [email protected].

It could transform your understanding of the true contribution that each of your online and offline channels are making.

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

Where do you go to get answers to your most pressing marketing questions?

Being tasked with finding answers to marketing questions to support your marketing decisions and advance your campaigns is no easy feat.

We are thinking of questions like:

– where are my most valuable customers coming from?
– what’s the best next offer I can make to each of them?
– how can I identify those dormant customers that are most likely to be reactivated?
– how much should I budget to spend in each of my online and offline channels?

In days of old you would most probably have fired questions like these at your advertising agency, and they would have responded using a smattering of science combined with a lot of judgement.

In today’s evidence-based world there are few one-stop solutions that can properly answer questions like these because to do so requires the right combination of marketing savvy, data, and data science.

However, there is something without which none of these questions can be answered, and that is the single customer view, where all data about your interactions with your customers are held.

For example, just taking the four questions we started with, you will at least need to know:

– how each customer was recruited?
– what their propensities are to buy from each of your main product categories?
– what sorts of customers are self-reactivating?
– all the online and offline events that preceded each of your customer orders?

So, what can we conclude so far?

That your single customer view needs to be skilfully designed to hold both the ‘raw’ facts such as details of a transaction, or a website visit, and also the ‘derived’ facts like a propensity to behave in a certain way.

But the single customer view is only part of the solution.

Our view is that the go-to resource you need is a combination of a customer data platform (the tool that builds the single customer view), with marketers to specify what it is expected to do, and data scientists to transform its raw data into sophisticated engineered predictions concerning your customers’ behaviour.

This is also the basis on which we have built our company. An understanding that marketeers need that right combination of people, technology, and data science to support their marketing actions and decisions.

If this is what you are looking for, then please email is at [email protected] and we will arrange a Zoom with our founder Julian Berry who will be delighted to discuss how we can help.

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

Could marketers view historical customer data like an archaeologist?

Could marketers view historical customer data the same way archaeologists view excavating a historic site? It may sound daft but we believe that the answer is a decided yes!

Archaeologists view a site that they are excavating as a series of layers. With each layer representing a distinct historic period –  this dating approach is known as stratigraphy.  They use this to associate different items of evidence with each other and can, for instance, differentiate Bronze Age pottery from Iron Age by how deep they find it in the ground at a particular site.

But the preservation of remains and artefacts within a layer tells much more. For instance, petrospheres are now known to have been used for smashing large bones to extricate the marrow. This is because these spherical stones and the broken bones have been found together in the same layer of Palaeolithic sites in the Middle East.

So, we marketers can look at historical customer data in a similar way. We can see what customer behaviour has taken place in each time period, in response to what stimuli, and learn vast amounts from that.

For this to work we need to make sure that our ‘stratigraphic’ customer data has been carefully collected and maintained. Clients need to ensure that all transactions, contacts and customer attributes [such as their source of recruitment and demographics] have not been discarded along the way.

What will this customer data tell us? What Tutankhamen can we expect to uncover?

If we take a group of customers recruited in a specific time period, we can look at the order value they on average provided in their first, second and third year from recruitment.  This will the help guide us to understand how much we can spend on recruiting them.
historical customer data acquisition chart

Now some of these customers will have only purchased once, and others will have purchased more often. Having uncovered the different groups we can start asking what differentiates them.

historical customer data retention chart

Often the source or channel of recruitment is the biggest factor in determining what their future value will be. Will a Facebook derived customer be worth more or less than one that comes from Google PPC? Their age at time of recruitment and their geodemographic can be of great significance.

Looking at the different customer layers we can start to ask questions about how the external environment has impacted their behaviour. Customers recruited in 2008 and 2020 cannot be expected to behave like customers recruited in more normal years. And when the economy shrinks, we can look to see whether demand has just been postponed or lost forever.

Could marketers learn a trick or two from archaeologists? Historic customer behaviour data sets are a gold mine if used properly.  To extract the value you will need both the customer data store, and the data archaeologists who can uncover the buried secrets.

In marketing we call these archaeologists data scientists.

We have developed our company UniFida along the lines of an archaeological dig; we collect and store our clients’ customer data (protected by UKFast, UK-based data centres ISO certified, PCI DSS compliant and secured to UK government IL4 standards) in our cloud-based technology, and we then deploy data scientists to extract meaning and learnings from that.

Please don’t hesitate to get in touch if you are sitting on a customer data site that needs careful ‘excavation’.

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

The identity resolution process: are customers turning into chameleons?

It may be noticeable that, like chameleons, they are becoming harder and harder to identify. And there is a reason for this. They are constantly changing their personal identifiers, like email, mobile numbers, or cookie IDs. The process to properly identify individuals we call “identity resolution”, and failures in identity resolution may sometimes have quite negative consequences.

Customers actively dislike not being recognised, for instance being treated as a new recruit when in fact they have been buying from you for years, or being sent the same message twice, and in addition to that there is a cost for the organisation with added communications costs.

Lack of good identity resolution processes also makes a nonsense of trying to calculate customer lifetime value or undertaking forward business planning based around your expected rates of recruitment and attrition.

 

So what does a good identity resolution process consist of?

We see it as matching all available personal identifiers, from every one of your customers, to get the best possible chance of joining your customer data inputs from multiple sources into actual customer records.

This used to be a relatively straightforward task when the main personal identifier was the postal name and address, although that in itself posed some considerable challenges.

With the usual mix of badly typed addresses, varying address structures, and incorrect postcodes we often find there is a problem just within name and address matching. In a recent case we found 25% name and address duplicates.

But the postal address is just one of multiple personal identifiers, each of which can change at any time.

We have all become identity chameleons, changing our mobile numbers, emails, cookie IDs etc with great regularity.

There is however a relatively simple solution – just keep hold of all the personal identifiers you have been able to link to each individual since you first recognised them, so that you have the best possible chance of identifying them when the reappear.

This is exactly what our cloud-based customer data platform does with the data it ingests; as each individual item of customer data is taken in, its identifiers are matched across the entire customer base.
an example of cdp identity resolution

If you think that you may have an identity resolution problem with your customer data, we can offer you a very low-cost solution; we can trial match all your customer data sources together in UniFida, and report on the amount of duplication that exists between them.

This will tell you how many customers you actually have, and how many duplicates you are carrying.

 

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

Are customer value metrics the backbone of your marketing?

It’s intuitively obvious that they should be, but what may not be so clear are which actual metrics you need, and how to connect them to different areas of your business decision making processes. Let’s take four key ways in which you can take advantage of customer value metrics.

 

1. High-level business planning

Your turnover is equal to the sum of the customer value provided in any period. So, to look forward to how your customer value is going to be provided in the future you need to be able to project from your current customer base, remove those that are going to attrite, and add those that you are going to recruit.

The metric to support this is the average value per customer in each year since they were recruited. So how much value in their first, second third year etc. This allows you to very easily roll customer value forward for planning purposes.

When you start from your planned turnover in say next year, you can then tell how much of that is going to be provided by the exiting customer base, and how much will need to be provided by how many new recruits.

You will also want to apply some assumptions about how value is going to be altered by improvements to the way you look after your customers, and then you will have the basics of a customer-based business plan.

 

2. Understanding which customer groups provide what level of value

You will be very aware that not all customers are equal when it comes to their level of spend with you.

So, you will need to dissect your average customer value by the type of customer they are. Factors such as age, gender, and product categories purchased can all be used to profile the value of your customers.

The benefit then is that you will know what groups to target your recruitment efforts at.

 

3. Examining the customer value provided by different channels and media

This type of analysis leads you directly to understanding the ROI provided by different channels and media.

Indeed, we like to use a metric which is the amount of longer-term customer value derived from every £1000 spent in a particular recruitment mode.

You can undertake this at a very micro level, such as individual media, or more macro level, such as a channel.

There is though a caveat; many customers are now recruited as a result of contacts from multiple channels. However, this does not prevent you from looking at the customer value obtained from each recruit for whom the channel has played a part.

 

4. Where to focus retention?

This is a harder question to answer as your higher value customers will often be the most loyal.

What you need to know is which of your higher value customers are more at risk than others.

For this you will need an individual level predictive model for risk of attrition with which to score customers, and find the higher value, higher risk, group.

 

Some conclusions

  • Understanding all aspects of longer-term customer value is critical for every successful marketeer.
  • To achieve this, you need a single customer view that can track customer behaviour through time.
  • You will then need to be able to obtain the metrics.
  • It won’t come as a surprise to regular readers of our newsletters that our customer data platform UniFida has been designed to provide most of the metrics we have been describing on demand.

In some cases further analysis will be required, and our data scientists are happy to help with this.

 

If you would like to talk to us about how to get the customer metrics you need, then please email to say when and how you would like to be contacted.

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

Attaining a multi-touch attribution strategy

‘Attaining a multi-touch attribution strategy that works is like looking for the holy grail’. This is one of the conclusions in a report just published by the CallRail Research Unit (click here to download the report).

A key finding from their survey was that ‘36% of marketers say that lack of insights into the effectiveness of tactics, or an effective attribution capability, is the most damaging factor to their marketing efforts; a further 25% ranked it the second most significant factor’.

It so happens that we have recently completed developing a multi-touch attribution capability and it’s now part of UniFida.

Attaining a multi-touch attribution strategy enables you to understand the relative influence, and ROI, of all your online and offline marketing channels and media.

We would like to give you a live demo and show you how it works. If you can spare us 30 minutes, please send us an email and suggest a convenient time for you.

 

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

Can you escape from Analysis Paralysis?

For many marketeers, a significant part of their day is spent pulling together reports from disparate data sources, and then trying to extract from them the metrics they need to unravel how their marketing is actually working. Usually with varying degrees of success and causing what we’ve come to know as analysis paralysis.

Well, if you are one of these people, we have a means of escape!

You may recall that our cloud-based customer data platform, called UniFida, neatly joins together all your online and offline customer information and builds a single customer view. It undertakes identity resolution, and links browsing and ordering activity to individual people.

We originally designed this tool to enable you to send very personalised communications to individual customers. But it also allows us to provide you with a complete set of marketing performance metrics. Serendipity happens!

The metrics we produce cover what we expect are your key concerns:

  • Customer metrics to tell you about customer acquisition, retention, and longer-term value
  • Campaign metrics to provide you with the results of all your direct communications with known individuals
  • And media metrics to show you how each of your media channels are contributing to the orders you are receiving (including social, display, PPC, email, mail, and SMS)

We recognise that you may not at this point in time need the whole suite of UniFida functionality, but you may be interested in UniFida Marketing Metrics as a standalone module, particularly when priced accordingly.

We believe that it can give you nearly all the metrics you need to manage your marketing at a very reasonable cost (and with us taking care of all the set up and configuration).

If you want to discover how you can escape analysis paralysis and get a quick understanding of UniFida, then contact us.

And if you would like to us to arrange a teleconference with you, then please email us with a good time to talk.

 

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

Predicting the future value of your customers

Did you know that by the time you on-board a customer you will be able to accurately predict their future value?

From which it becomes clear that the decisions you make at the customer recruitment stage will determine that key metric of future customer value.

These are typically decisions about the recruitment channel and tactic you use, the types of customer you are targeting, and the nature of the proposition you are making to them.

Now you should also take into consideration the fact that a large number of customers that businesses recruit will yield negative value after the costs of recruitment have been deducted, whilst others will be strongly positive.

Predicting the future value of your customers

So, what as a marketer, should you do about predicting the future value of your customers?

  • First stop focusing on cost per acquisition; it’s the wrong metric to be guided by.
  • Next, we suggest that you should take a multivariate approach so that you consider all the factors together that define customer groups in order to focus on the ones that will bring you value.

We have recently been helping a substantial life insurance broker do this and the result has been transformational; for instance, they can now balance factors like the risk of attrition against the amount of monthly premium paid. They have found that a substantial number of their marketing tactics are yielding negative customer value and have had to be abandoned.

If you would like to discuss how to target your customer recruitment for longer term value then please contact us.

If you would like to read a case study about how we did it then please read our post:

 

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.

How a customer data platform uses data for decision making

The maxim ‘knowledge is power’ has held good for many years but that power also can be democratised when knowledge is shared. Shared knowledge obtained from data, leads to a common understanding of how a business is working, and from this a more effective, faster and smoother decision making process. No more meetings starting with that obstructive statement ‘I don’t recognise the numbers’.

 

So, how does a CDP use data to enhance, accelerate, and democratise decision making?

Several reasons combine to contribute to the result:

1. A CDP will build peoples’ identities using data coming from many different sources.
This means that individuals may be matched on their postal address, their email, their mobile, their cookie ID and more. The identifier, we call it the permanent URN or PURN, for an individual will be fixed in the system and any new data that matches to it added to the customer record. From this we achieve a finite, and at any moment in time, fixed number of known individuals in the system. We can no longer disagree over customer volumes or the data that is attached to them.

2. All the data that arrives goes into a shared data schema.
This means that the data definitions are constant as well as the values within them. A customer data platform can have only one set of values for gender or marital status for instance.

3. The CDP does not dispose of data unless required to do so under GDPR or because it has no conceivable value.
When a CDP is being set up historic customer data is loaded into the system, and from that point on data will be augmented. This data usually includes details of on-line activity, when it can be matched, as well as transactions undertaken, and contacts made through any channel both inwards and outwards.

4. A good CDP will check the data feeds as they arrive for consistency of their layout and content.
Feeds that do not conform are rejected before they go into the customer data platform. In some cases, such as when we are dealing with names and addresses, they may need to be improved using matches to external verification files like PAF.

5. A smart CDP will go far beyond just recording the input data.
It will start to build what we call engineered data. This is data derived from the raw data that comes in to the CDP. It may be a calculation of lifetime value in the first year since acquisition, or the result of applying a customer segmentation or a propensity model. Engineered data fields are then updated each time new data arrives for an individual. It is often the case that charts and reports are built from the engineered data rather than from the raw data. For instance, to answer a question like what is our customer retention rate we need to have an engineered data field that marks whether a customer who purchased in period A also goes on to purchase in period B, the periods being linked to when the individual first appeared as a customer.

6. The CDP will allow access to all users in a company who want to see that single common view of the customer.
This may be by way of dashboards or on-line reports, or because they have the tools to extract data directly from the system. The dashboards may be tailored to each individual user or be common to a department or a whole organisation. But whatever charts or tables they contain they will all be derived from the same common but constantly updated CDP. This means that they cannot disagree because both the data they are drawn from is common, and the definitions that they use are shared.

 

And what types of understanding can be obtained from the CDP?

Having developed a shared, consistent, and complete customer data source, the CDP can be put to support a multitude of uses. What follows is a description of some of the more common ones, but in reality, there is no limit on the kinds of outputs that can be achieved, particularly when the CDP is aligned with a clever data visualisation tool like Tableau.

1. Supporting AI.
Underneath all the hype about AI is the need for good data to support it. If an AI tool is to learn from a flow of data being fed into it, that flow needs to be unchanging in its composition, and accurate to the point of perfection. A CDP is perfectly designed for this role.

2. Tracking the overall customer picture.
Managers looking after customer acquisition and retention will have an almost unlimited number of questions they need to have answered. Some of the most typical are:

  • What volumes of customers are we recruiting through which channel?
  • Do the different channels and media sources provide customers with different characteristics and different longer-term values?
  • How do the different social media channels contribute to my customer volumes?
  • From which geographies am I recruiting my customers?
  • What is my level of second orders and year on year customer retention?
  • What behavioural segments do my customers fall into, and what do they look like when profiled by demographics and lifestyle?
  • Have the characteristics of my customers altered over time?
  • Are there some customer groups that provide such low value that they are not worth the cost of recruitment?

3. Tracking the product picture.
Every business knows the high-level numbers on product sales but beneath this high-level view are many interesting questions, for example:

  • Are different types of customer changing the mix of products they buy?
  • Do different channels lead to different products being purchased, and to different product values being chosen?
  • What is our best recruitment product?
  • How loyal are customers that are first attracted to different products?
  • Given that we know the first product purchased by a customer, can we predict what a customer is most likely to buy next?
  • If we deduct the cost of marketing and cost of goods, how profitable are our different products?
  • Can we build a time series model to predict overall sales of my products based on a combination of customer information, and marketing history, combined with external factors?

4. Next up, understanding the impact of marketing.
A strong case can be made for the assertion that without a reliable CDP the value of marketing will always be an unknown. For instance, if you cannot attribute sales that come in via the internet to prior marketing communications how can you justify the cost of those communications? Or if the longer-term value of customers cannot be measured how can you justify the cost of recruiting them beyond the value of their initial purchase? Some of the many uses of the CDP for marketing have been detailed above under customer and product understanding, but there is an additional layer which comes from being able to link marketing activity in its many guises to an outcome in terms of customer value. Some examples are:

  • Linking expenditure on social media to actual customers recruited and the value they subsequently generate. Very few companies spending fortunes on social media take the trouble to do this, but with the right digital analytics combined with the CDP this can be quite straightforward.
  • Examining campaign results not just from the overall value obtained, but also investigating what types of customers they attracted, and what different longer term values they brought with them.
  • Providing the data to help understand a complex sales funnel where prospects drop out at different stages; in these cases, there is a need not only to understand the impact of the different processes on drop-out levels, but also what types of prospects are better at surviving the overall funnel process.
  • If there is a customer retention problem, then this can be evaluated in terms of lost revenue, and from that budgets provided for retention activities that can then be tracked, using control groups held in the CDP, to find out which provide the best ROI.
  • When a marketing budget is complex and spread over many different activities then there is a need to untangle the impact of the different marketing activities and prioritise the way budget is allocated to optimise results. This requires building an understanding of the relationship between spend in a channel and the usually diminishing results achieved as spend is increased. This is often called a saturation curve. For this kind of analytical activity the underlying data is found in the CDP, although the subsequent analysis is done outside it with different tool-sets.

 

To wrap it up

It would be presumptuous to claim that a CDP can solve all marketing problems, but without doubt it can ensure that knowledge is shared, and the data required for intelligent decision making made readily available. A CDP can be perhaps viewed as the necessary foundation stone for all successful marketing organisations.

 

Contact us if you’d like to know how we can help your organisation.

UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.