How does a customer data platform work?

Ingesting and integrating data

So how exactly does a customer data platform work? The first element in understanding how a customer data platform works is ingesting data. CDP’s ingest customer data from multiple sources. Typically, these will include website data, paid digital, transactional, direct mail, retail, email, and call centre. All data received by a CDP will relate in some shape or form to a customer. The data is usually sent to a CDP using an API or via an SFTP site.

Customers have multiple identifiers and these change over time, such as mobile phone number, email address, cookie ID, postal address, customer reference or landline number. This data is collected, and these identifiers are used to generate a single customer view also known as ‘Identify Resolution’. For example: if someone logs into your website with their current email, but with a different cookie ID, then the new cookie ID is added to that particular customer record on the assumption that they are using a new device. Equally, if a new transaction record is received with the same customer reference, but a new address, then a new address is added on the basis they have either moved or added an extra residence.

As new data is ingested, each record goes through what is called the ‘purning’ process. This is the stage at which the record’s personal identifier(s) are matched against all other customer records that are held in the CDP until a match is or is not found. At this point the data may be matched into an existing single customer view or a new one created. Each recognised customer is given a permanent unique record number or ‘purn’.

Identity resolution

Is at the heart of a CDP and is central to all the rest of its functionality. A good CDPs’ functionality is rooted in the knowledge that people have multiple identifiers, and that these identifiers can all change. Over time many or all of these identifiers are likely to change for an individual. The CDP should keep a history for every one of every version of these, although regarding the latest versions as most likely to be current. This collection of identifiers is what it calls on to build the single customer view.

The data in a CDP is held in what is called a schema. This is the way in which the data is organised. Every organisation using a CDP will need their own schema although within an industry, schemas will have a lot of similarities.

Engineering derived data

Engineered data is important for the value it provides for selecting specific customer groups for communications or developing customer insight. It can comprise any variable that can be calculated using an algorithm or other means from the raw data in the customer data platform.

Data engineering can take many forms, from simple examples like banding variables such as age, to more complex ones like keeping a counter on customer’s total historic value. A major use of engineered data is in developing and recording scores derived from algorithms such as propensity models.

An example of an engineered data field is where we want to know what each customer has contributed to a business after the cost of acquiring them. We can then:

  • Use historic purchase data for each individual in say their first and second year since recruitment
  • Deduct the cost of acquisition which can be derived the channel they came in from
  • Deduct the cost of communications sent to them in the same period which is held in the contact history area
  • Calculate an individual customer contribution

Engineered data is updated at an individual level every time a relevant event happens; so, each new home shopping purchase, eCommerce transaction or physical retail transaction can lead to a changed score in the engineered data section. A great benefit of engineered data is that it allows you to base axis for charts or selections for campaigns on these additional variables.

Analysing customer data

A CDP is essential for gaining a full and accurate understanding of customer behaviour. For instance, without a CDP that combines web browsing history with transactions, it would not be possible to understand the relationship between the two. Again, if individual contact history is not held against a customer record then the effectiveness of campaigns that are sent to the customer, and to which the customer may respond through different channels, cannot be accurately measured.

The CDP builds the single customer view, and it is against this that customer analysis can take place. It provides the dataset that becomes the one authoritative source of information about customer behaviour for an organisation. With this in place decision makers have a firm basis on which to proceed.

There are so many aspects to the analytical tools that can be used to analyse customer data that there is little merit in trying to list them all. Some are built into the CDP and others require data to be first extracted from the CDP and then transferred to them. What matters is that they have the best possible customer data set to analyse.

So, the results from customer analysis form the basis on which key decisions about customer marketing can be made. These include such areas as:

  • Customer acquisition (targeting and channel choice)
  • Digital planning
  • Product development
  • Customer relationship management
  • Salesforce management
  • Pricing

Even corporate mergers and company valuations.

Given how important these decisions are, it makes good sense when designing a CDP to first start with a list of the kind of results that will be required from customer analysis so that for instance data is held with sufficient granularity to make these possible.

Connectivity to external systems

The CDP can support other systems in their personalisation and management of customer communications. Typical examples are:

  • Providing customer selections for email marketing systems
  • Customer segmentations for web personalisation technology
  • Names and addresses for postal marketing
  • Target audiences for social media

So just as the CDP ingests data from multiple sources it also provides selected data to external systems. These connections are usually made via an API or via transfer of data to an SFTP site.

Delivering personalised customer experiences

Within the CDP we expect to find functionality for the selection of specific customer groups either on a one-off or on a recurring basis. These groups are usually selected for output to external systems that manage the actual communications. The selections themselves can be simple based on Boolean logic rules, or they may be more complex based on propensity scores applied within the engineered data. They can also be based on triggers, such as a new customer having just been recruited.

The CDP needs to enable these different types of selection, and crucially record what contacts each individual customer has been selected for. Functionality is also required for test and control, and for including source codes with the selection.

Associated with delivering personalised customer experiences needs to be functionality for measuring the results of campaigns. This is often automated within the design of the CDP and should always include the ability to attribute results such as orders back to campaigns, even if they respond through different channels.

What are the costs for a customer data platform?

What is a customer data platform?

So what exactly is a customer data platform?

As customers we generate massive volumes of data as we engage across multiple channels using different devices which makes it challenging to capture, integrate and activate this data effectively.

Data repositories are often siloed and not integrated with each other or allow easy transfer of data to marketing platforms. Let us now throw in some GDPR and updates from Apple with identifier for advertisers (IDFA) and the deprecation of third-party cookies by Google.

Today’s customers simply assume that your company knows and remembers who they are, what they have done, and what they want, always and across all channels. Their expectations are high, and tolerance is low. So it is not surprising to see that many marketers have made a unified customer experience their highest priority.

What’s the problem with data?

Not having a single customer view creates many challenges including:

  • Making it more tedious to activate campaigns to the right audience and report on them in a timely manner.
  • Degrades customer experiences.
  • Introduces privacy concerns.

Marketers and marketing technologists know that gathering and acting on unified customer information is not easy. In fact, only a small percentage of companies have achieved this and can truly operationalise their first party data. The rest are battling with technology, strategy, budgets, organisations, staff skills, and other obstacles to success.

Traditional methods for collecting that data into unified customer profiles, such as an enterprise data warehouse, have failed to solve the problem. Newer approaches, like “data lakes”, have collected the data but failed to organise it effectively and enable marketers to activate the data into owned and paid marketing channels.

The Customer Data Platform is an alternative approach that has had great success at pioneering companies. The process of collecting and unifying the data is known as identity resolution which is a core building block for enabling better customer experiences and optimised marketing effort. A CDP puts your marketing team in control of the data unification project, helping to ensure it is focused directly on marketing requirements.

CDPs apply specialised technologies and pre-built processes that are tailored precisely to meet marketing data needs. This allows a faster, more efficient solution than general purpose technologies that try to solve many problems at once.

Customer Data Platform Definition

“A Customer Data Platform is packaged software that creates a persistent, unified customer database that is accessible to other systems”.

This definition has three critical elements:

1. “packaged software”: the CDP is a prebuilt system that is configured to meet the needs of each client. Some technical resources will be required to set up and maintain the CDP, but it does not require the level of technical skill of a typical data warehouse project. This reduces the time, cost, and risk and gives business users more control over the system, even though they may still need some technical assistance.

2. “creates a persistent, unified customer database”: the CDP creates a comprehensive view of each customer by:

  • Capturing data from multiple systems.
  • Linking information related to the same customer.
  • Storing the information to track behaviour over time.

The CDP contains personal identifiers used to target marketing messages and track individual-level marketing results.

3. “accessible to other systems”: data stored in the CDP is then made available to other marketing systems for analysis and to manage customer interactions.

What should a customer data platform do?

In essence, a customer data platform combines all your customer data from online/offline sources and unifies this into a single customer view to enable cross-channel activation and personalisation.

A CDP should integrate into existing and future marketing/advertising technology enabling you to decide which channels to communicate with your customers.

It should enable automated reporting of activity on your key marketing metrics. And of course, it should support GDPR enabling you to check customer consent, action subject access requests and the right to be forgotten.

How does a customer data platform work?

In praise of use cases…

(or ‘anvandningsfall’ as they were originally termed)

Back in 1987 a Swede called Ivar Jacobson presented the first known article on use cases as a means for capturing and specifying requirements for computer systems. He didn’t much like their original long Swedish name and eventually settled on ‘use case’ which has since been universally adopted.

So why are we singing their praises?

Use cases do not require technical knowledge, they allow your teams to collaborate on the desired business outcomes and uncover gaps. One of the key things with a use case is it ensures your stakeholders have defined the business need and, how the activity will be measured.

An example of a marketing use case is “Use data to deliver relevant, personalised omni-channel campaigns in order to increase revenue and reduce marketing costs”. The use case is pretty straight forward. The brand wants to communicate with their customers across multiple channels in order to generate revenue and potentially reduce wasted marketing spend.

Many businesses fail to develop core use cases to solve a problem or deliver on a strategy. By developing core use cases, which are prioritised based on the business goals and can be measured, it will give you the north star to focus on and deliver against your goals.

We see at least five stages in the process of successfully introducing marketing technology where they are of crucial importance.

First by going through the discipline of articulating and documenting use cases a business can clarify exactly what they want this nebulous item, a marketing system, to actually do.

It provides a non-techy way for the requirements to be mapped out so that the user community can articulate step by step what both it and the system are expected to do, and what the outputs should look like.

It also allows for consideration of time. When and how quickly should processing happen including volume. Thus, allowing the system providers to get a handle on whether for instance they are dealing with ten thousand or a million customers.

Given that nowadays almost all martech is purchased off-the-shelf rather than being built inhouse, the combined use cases can help start the process of vendor selection. Rather than being told a long list of the glossy features that can be delivered by the martech salesperson, most of which you don’t want in the first place, the company can factually check whether the system being proposed can actually do what you require.

Next, the use cases can feed directly into developing the business case. If for instance you are going to be able to do A that you couldn’t do before, how much customer value are you going to be able to generate compared to where you are now. Or alternatively how much staff time will be saved using the new tool to deliver B more quickly?

We find that business cases for martech generally span across four key areas:
1 The incremental revenue generated by being able to do something that was not possible before.
2 The cost of time saved by using a better tool to deliver something more quickly.
3 Reduction in technical debt by streamlining and unifying data and platforms.
4 Reducing reputational risk by having clear GDPR measures in place

Once past the business casing stage, many organisations will want to start with a live proof of concept or POC. If you select a few areas where the new technology should add value, and where it can be set up and configured quickly (please note I am not writing LHF!) then a POC can be put in place.

There is no better way to finally confirm that everything works from the technology to the customers responding to it. In addition, a live POC that works, gets quick buy in from all levels in an organisation. The POC will also pick up on what is not working and enable you to put it right.

And finally, when the full martech needs to be set up and configured, the developers can take the use cases as the specification against which they are going to have to deliver. The company can sign off the configuration as done when the use cases work.

At UniFida we like to help our clients with developing their use cases at the start of the process of introducing a customer data platform. We do this for all the reasons articulated above, and incidentally it helps us understand quickly whether we can in reality deliver what you need.  Having developed several client use cases, we can help stimulate your thinking around what they might provide.

Our offer! We have made a decision not to charge for this kind of consultancy as it helps you understand what you need the technology to do, and for us to understand what we may be called on to deliver.

Please do get in touch if help with developing use cases for a customer data platform is what you are looking for.


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.


CDPs provide efficiencies as well as effectiveness…

…but to realise both takes time.

We have been looking at an interesting report called ‘The State of CDPs, Q3 2020’ by Treasure Data and Advertiser Perceptions. The research is based on 101 respondents working for larger US companies.

The CDP use cases for the marketing effectiveness are generally well known, and this slide does not provide any real surprises:

What was more striking though were the improved efficiencies experienced by companies using a CDP.

These efficiencies improve as companies have more time to get used to having a CDP.

To get full value from a CDP a company needs to adapt its marketing processes around it, and this takes time. To take a common example, there may have been one team dealing with owned outbound channels such as emails and direct mail, and another with paid digital advertising such as display, programmatic, SEM etc. and, another team managing the website content, optimisation and of course the data. In order to deliver the optimal messaging, customer experience and drive business value, all of these channels need to be merged to deliver a unified customer experience.

One area that does not change with CDP tenure is the freeing up of IT resources. This is because once the feeds into a CDP have been organised, and the CDP configured, IT should be able to take a step back and let the marketers take over. This all happens in the early stages of introducing a CDP.

CDP technology is an enabler allowing marketers to do things differently, and this change process will inevitably take time. This delay factor needs to be built into the calendarisation of benefits when developing the business case for a CDP.

This is a major component which is often overlooked by businesses when considering marketing or advertising technology such as a customer data platform, the people who operate and optimise it. Do they have relevant skills and experience to maximise the investment? Have you allocated time and budget to ensure a consistent coaching and development programme is in place?

Hence the considerable increase in satisfaction with CDPs seen amongst companies with more than two years’ worth of experience of using them.

If anyone reading this newsletter is at the early stage of considering whether they should introduce a CDP, and would like help establishing the use cases for one, and quantifying the benefits, we would be only too pleased to offer support, without any charge. We have worked on many CDP business casing exercises and can help fast-track you through the process. We also provide in depth training and support and hold your hand at every step to help deliver your goals.


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.


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.

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 tying 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.

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.


We are told that first party data is taking centre stage!

This is according to a just published report from the Winterberry Group ‘The State of Data’; to be fair it does only cover US marketeers but trends there are often repeated in the UK.

The reasons behind this are not too hard to guess:

– the phasing out of the use of 3rd party cookies
– the better returns to be got from looking after existing customers compared to recruiting new ones

Respondents highlighted use cases associated with leveraging and deriving value from first party data as those that will capture their foremost attention in 2020.

Without wanting to blow our own trumpet too loudly, the combination of UniFida customer data platform technology and data science covers all the areas inside the red box.

Please try our short survey to find out if you should be considering introducing a customer data platform, and please email us on info@unifida.co.uk if you would like to arrange a Zoom chat with our founder Julian Berry to check whether we may be able to help you put first party data centre stage.


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?

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 info@unifida.co.uk 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.


Do you really know whether your company should install a customer data platform?

Customer Data Platforms (CDPs) are taking the marketing world by storm – the Customer Data Platform Institute projects that marketers will spend $1.3 billion on them in 2020.

But the important question for your company is whether you would really benefit from having one?

So, what do CDPs really do? At a very high level they:
– ingest all available sources of online and offline customer data and build a deduplicated single customer view
– provide the capability to profile and segment customers
– enable personalised and consistent communications to take place across all channels by connecting your marketing technology
– support you in visualising customer performance

We have devised a simple 10-point questionnaire to help you understand whether your company could benefit from a CDP. It won’t be telling you whether should definitely should have one, as you will need a business case for that, but it will tell you whether CDPs are worth investigating.

QUESTIONNAIRE

If you want to start to find out more about what a CDP could do for your company then please order our free e-book CLICK


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.


53% of marketers don’t have a cohesive strategy for Martech…

… and only 20% are implementing one!’ This is the headline of a report we have just received from Demand Lab, a technology focused marketing consultancy.

It may be an exaggeration, but there is some truth here. Many B to C marketers have made their decisions about purchasing Martech in a very piecemeal way, and ended up with an extensive but uncoordinated marketing toolkit.

Each technology item has been purchased on its own, to do a specific job, without adhering to an overall strategy.

And their difficulties are compounded by the way that the Martech vendors usually present themselves:

– Confusing websites that don’t explain fully what the technology does
– Opaque pricing arrangements
– Features, not solutions focused descriptions
– Little explanation about how the systems are to be configured
– Or what level of internal IT support you need to make them work

We believe that the overall Martech strategy for most medium sized companies does not need to be over complicated.

There are some core components that should be the foundation of any Martech strategy, such as these:

We have marked some of these boxes yellow because most marketers have these already; the problem often is that they don’t naturally join together.

The email service provider may not know what is going on in the website. The call centre doesn’t know what the mailing house has sent out to Mrs Smith when she calls in. The retailers don’t know what kind of customers they are dealing with.

This explains why we decided to go into the customer data platform (CDP) business. To integrate all this customer information and build a comprehensive picture of every customer you are in contact with.

A CDP works best when it’s set up in conjunction with, or has built in, personalisation technology that automates individual messaging via your website and your email service provider.

The personalisation has much more meaning when it is based on knowing what type of customer you have been in the past. Not just on what you have looked at on the website in the last few seconds.

The CDP can then also segment the customer base so that the offline mailing house or call centre send out relevant targeted messages.

But the CDP does much more as well. Having all your customer data in one place, you can measure the effectiveness of every marketing activity as well as track how your customers are performing in terms of value and loyalty over time.

It can inform your recruitment strategy by showing you how different channels bring different types of customer. Show you how they are working in combination. That way you can escape from last click order attribution and attribute the correct value to the role each channel performs.

Every company is at a different point in their journey to getting the Martech that is right for them.  If you would like to chat to us about where on your journey you are now, and where you need to go, we are here to help at no cost to 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.


Could marketers learn a trick or two from archaeologists?

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 historic 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.

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.

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.

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.