How does a customer data platform work?

how does a customer data platform work?

How exactly does a customer data platform work, and help marketers leverage data to gain a better, more accurate understanding of customer behaviour?

Ingesting and integrating data

The first element in understanding this 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?

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.

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?

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.

Why your own first party data is so important?

There are many reasons why first party data is important, but your recognition of it may be at risk of being drowned out by the clamour of people selling recruitment media, particularly digital and programmatic media.

To us the case for first making best use of your own customer data trumps all other media purchase decisions, and for very good reasons:

  • it’s free and uncontrovertibly yours (as long as it’s properly permissioned)
  • it allows you to develop very personalised relationships with each of your customers, and hence unlock as much value as is possible from them
  • it can help you understand what is really driving your new customer recruitment, particularly when multiple online and offline channels play a part in your recruitment marketing
  • it can support your overall business planning based on understanding the longer-term value provided by each customer segment

To allow you to obtain that customer value you need to ensure that your single customer view contains all your customers’ online and offline behaviours, linked by all the available personal identifiers.

You also need marketing technology that joins all this together, so that there is one complete version of the truth about each customer that can be used by all your marketing applications.


This is why we suggest you need to consider installing a customer data platform or CDP

To help develop an understanding of what a CDP can do for your marketing we offer three complimentary services.

  1. Data duplication testing: Identify how many duplicate customer records you have. Understand the impact of wasted spend on marketing.
  2. Suppressions run report: Identify and suppress individuals who have moved away or deceased.
  3. Business casing exercise: Identify and develop use cases and financial evaluation. See the opportunities and map out the ROI prior to any commitment.

Contact us to find out how UniFida’s Customer Data Platform could add value to your business.


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.

9 stepping stones to better leverage customer data

Wondering how to better leverage your customer data? For many, the journey from being a basic user of customer data, for example just providing lists for campaigns, to being a fully customer-orientated organisation, is perceived as being full of risks and traps for the unwary. As a result, the journey is often halted before it is even started.

However, you are not in uncharted territory, and by following some clearly defined steps you should arrive at your destination without too many damaging hiccups.

But before you start, you must regard it as a journey where you don’t know clearly what the destination will look like, and you cannot map out in advance with any certainty all the different benefits your organisation with see when you leverage your customer data.

1. First off you will almost certainly be asked to justify the cost

Because the benefits of using a customer data platform can come from many different areas of the business you will need to bring together multiple use cases – they can range from making existing activities such as email campaigns more effective through personalisation, to understanding how much you can afford to spend on recruitment because you know the longer term value of different types of customer. Knowing how each area of the business works now, you can estimate the percentage gains from improving effectiveness or introducing efficiencies. At this stage they have to be estimates, but you can get colleagues to help you provide well-judged ones.

2. Next, focus on building a robust first party data platform

A first party data platform should include both online and offline customer activities. Don’t leave out online browsing data, customer contact history, or email opens and clicks. The platform needs to be updated very regularly and be open to integration with other systems such as email service providers. There is a lot of detail to be covered in this stage such as the customer data schema, and GDPR requirements, but always err on the side of including all available granular customer data as long as it is structured and can be linked through personal identifiers to the customer record.

3. As part of developing the first party data asset you will want to manipulate some of the raw data material into something more usable

We suggest developing a few key customer variables that are derived from your data inputs. For instance, customer lifetime value, and customer recency, frequency and monetary value can be of enormous use when planning recruitment or making selections for campaigns. You won’t need more than a handful of these derived variables at the start, so focus on those that will make your customer marketing activities work better.

4. Jump in and start testing new ways of undertaking your marketing

It might be that you start by testing the impact of segmenting your customer base, and giving different parts different treatments, or you could decide to reactivate some of your dormant customers with a carefully designed special offer specially targeted at those most likely to be reactivated. Whatever you do, focus on building a control group to shadow every test, so that you can properly evaluate how much uplift you have managed to achieve. And for every test carefully record what offer was made with what graphics, and how the target audience was selected.

5. Never stop testing

Even in a mature state you should expect to spend at least 15% of your marketing budget on tests. You will never run out of things you want to try out. If you test too little you will quickly run out of routes to move forward. And tests should take risks; we heard recently that 3D postal packages outperform flat ones – how strange is that?

6. Leverage your customer data asset for longer term business planning

When you understand the cost of customer recruitment, the value per customer, and their rate of attrition you can start to build a business development plan based around real customer numbers. So to increase turnover by £X next year, you will have actual customer numbers to recruit, and you will know how much that will cost, and over what timescale the value comes back.

7. Keep on investing in customer analytics

You may want to be able to project forward from a first order to predicting how much a customer is going to buy, and from this how much you want to spend on him. Equally if you have several competing brands, or different product categories, you may need to be able to predict which offer is likely to get the most valuable response from each customer. Customer analytics and marketing tests go hand in hand, and if you give up on either you may find yourself moving backwards.

8. Keep your sponsors engaged and behind you

They will need to see the big picture as you move forward, explained in relatively simple terms. Each quarter you will have spent £X, and got £Y back in terms of enhanced customer value. Sometimes £Y will be less than £X because you have been investing heavily. Don’t let this put you off; as long as you can explain clearly how that investment will pay back over time your sponsors will remain on-board.

9. And finally ensure sustainability

This means building a team that can survive without any one of its members, including yourself. It also means recording everything you do, the messaging, the images, the way campaigns were structured, the selection tools you used, the routes you chose for order fulfilment etc. All too often good people leave an organisation with little recorded evidence of what they have done and thus create a knowledge chasm that can take many months to fill.

If you want to improve how you leverage customer data and are looking for support, we are here to help. We can help you develop your business case, build a customer data platform, undertake customer analytics, and evaluate results.

We also offer three complimentary services to help you develop a better understanding of what a CDP can do for your marketing and business:

  1. Data duplication testing: Identify how many duplicate customer records you have. Understand the impact of wasted spend on marketing.
  2. Suppressions run report: Identify and suppress individuals who have moved away or deceased.
  3. Business casing exercise: Identify and develop use cases and financial evaluation. See the opportunities and map out the ROI prior to any commitment.

Contact us to find out how UniFida’s Customer Data Platform could add value to your business.


Do you know how much your customer duplicates are costing you?

Deduplication may not be the stuff of everyone’s dreams, but it could turn out to be more interesting than you expect.

How much your customer duplicates are costing you?

How many duplicates can you expect to find?

Our rule of thumb is that within any single customer system there will normally be between 5% and 25% duplicates.

However the more ways you have of identifying an individual, the higher the level of duplicates normally uncovered. For instance, if names and addresses can be combined with email or mobile number, many records can be brought together that otherwise would have been kept separate.

There are no rules of thumb however about the level of duplication between different customer systems held by the same organisation; but as an example our recent work with a media company selling a range of direct to consumer services revealed that for every 100 customer records held across their systems, there were in fact a net 75 individual people.

So why does this matter?

Perhaps the most obvious reason is that deduplication will stop you sending two communications to a proportion of your customer base.

Just stop to think just how irritating it is to have to open or delete two emails from the same source with the same content.

And then, if you are using paper and post, there is a big cost implication of not getting the deduplication right.

The second reason is GDPR. How will you handle individuals’ requests to be forgotten when there are two versions of these peoples’ records? And how foolish would you feel when sending customers copies of the data you hold on them when clearly it came from two separate sources?

But probably the most interesting aspect of deduplication comes when you pull data together from across different systems and sources.

Mr Smith who buys holidays, and is on a dating site you run, has a distinct profile; so does Mrs Smith who buys wine and cooking equipment, and so probably likes entertaining at home.

How much your customer duplicates are costing you? So whether you have a single customer file, or customers spread across several systems, the case for deduplication is clear, but just how clear it is can only be quantified when you have matched all those customer records together.

To find out more about Unifida can help your business please contact us.

Has GDPR ignored the elephant in the database?

So has GDPR ignored the elephant in the database? ‘Personal data’ is defined in GDPR as ‘any information relating to a person who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that person’.

So each of us can be seen as ‘bristling’ with multiple potential identifiers, any or all of which may be stored by organisations using our personal data. And to add another layer of complexity, most of the commonly used identifiers, like email addresses or mobile phone numbers, may change on a regular basis.

All of us, as data subjects, can ask any organisation holding their data,for their personal data to be deleted, or transferred, or not to be used for marketing communications, or for profiling, or sold to anyone else etc. etc.

We may also change our minds about how our data can be used, and most probably forget what we have requested in the first place, because it’s not at all important to us.

So, for example, using our name and address as our ID, we request that organisation X does not profile our data, whilst using our email we ask to have our data deleted, and via our mobile phone number then expect to have our recent order traced.

GDPR tacitly assumes that persons about whom personal data is held can each be recognised uniquely, across all the identifiers they care to use, and as they change identifiers over time; and that from this basis rational interpretations can be made of their instructions.

This is evidently a delusion.

As vendors of a technology to build single customer views we know how difficult the identity problem is. The normal ‘shrinkage’ when we deduplicate a customer base across just say a couple of identifiers is around 20-25%; the more the types of identifier the greater the chance of duplicate records.

The technology we have developed to try to solve the problem is called UniFida, and it approaches the question of personal identifiers in a rather different way. It assumes, correctly, that all our common identifiers like email addresses, mobile numbers, cookie IDs etc. will change over time, and that individuals may have multiple versions of them.

So, it stores a history, for each individual, of all the identifiers it has been able to link. When an identifier arrives at UniFida as part of an on-line or off-line data feed, it searches the entire library of identifiers to see if it can get a match. In this way, it brings as much information about an individual together as is possible.

Has GDPR ignored the elephant in the database? To find out a little more about Unifida please contact us. It may make complying with GDPR a little bit more possible.