Why are we now reselling Fresh Relevance’s personalisation capabilities

Why are we now reselling Fresh Relevance’s personalisation capabilities alongside UniFida’s customer data platform?

One of the key uses of a customer data platform is to ensure that decisions made about how and what to communicate with each individual customer across any channel are based on one consistent single customer view.

UniFida’s customer data platform provides the single customer view, combining both online and offline data, and we have partnered with Fresh Relevance to use this for website and email personalisation.

So, what does this mean in practice?

Let us provide some quite simplistic examples (we are sure that you will be capable of creating some much better ones):

One of your dormant customers, Mr Smith, is browsing your website and we recognise him from his cookie ID, or because he provides an email address; Fresh Relevance has already been provided by UniFida with detailed information about Mr Smith’s past purchases, and can use that to remind him that he often prefers category ABC. And it does this in combination with a valuable offer should he decide to reactivate himself after not ordering for so many months.

Another customer Mrs Cook has filled her basket on several occasions but never gone as far as making a purchase on line. UniFida knows that Mrs Cook is in reality a good customer who normally orders by phone. The website, powered by Fresh Relevance, then offers Mrs Cook the opportunity to chat to an agent, and to turn her basket into an order having discussed her potential purchase with one of your agents, who understands when chatting to her what she has liked to purchase in the past.

In a third case you decide to reward previously loyal customers who have not so far ordered this season. UniFida knows how much Mr Jones usually spends at this time of year, so Fresh Relevance can personalise an email that gives Mr Jones a discount based on his previous season’s spend. In this way the loyalty bonus is only offered to customers who have not ordered, and not wasted on those who have done already.

In reality there are thousands of different ways in which an experience personalisation tool like Fresh Relevance can work with a customer data platform like UniFida. The only limitation could be your fertile imagination’s capacity to come up with much smarter ideas.

What we like to do is to put these tools in your hands, so that you can experiment and find out what really works best for your customers. One thing we do know is that personalisation, when truly relevant to an individual customer, works wonders for your sales.

If you would like to talk more about personalisation and how to implement it for your business, please get in touch!

 


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 this is the case, 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 have written ‘The Marketers Customer Data Platform Resource Book’; and this is now available free as an e-book.

David Raab, Founder of the Customer Data Platform Institute, wrote of it ’This concise introduction provides clear answers to CDP questions. It will help many marketers and their technologists take the next step in their CDP journey’.

If you are thinking about possibly taking the next step, then please download your free copy of our booklet “The Marketers Customer Data Resource Book“.

 


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.


Nine stepping stones for a customer data pilgrim!

Wondering how to become a customer data expert?

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 ways that making good use of your customer data asset will benefit your organisation.

  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, that includes 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. Start using 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 fulfillment etc. 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 be a customer data pilgrim, 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 can also offer you a free copy of ‘The Marketers Customer Data Platform Resource Book’ which we published recently to help people starting out on the customer data journey.  Simply sign up for our mailing list and we’ll send you a link to download the Resource Book.

Why most ‘CRM’ systems are not really what they claim to be!


On the surface CRM systems give the appearance of covering most things you might need when you are looking for technology to help you manage relationships with customers.

But the reality is that they have been designed to only deliver the basics.

Yes, they manage what they call ‘contacts’ but these are usually only matched together using email addresses. The much bigger and key role of identity resolution is left unresolved.

Customers in fact have many different identifiers like mobile phone numbers, cookie IDs, postal addresses, account numbers etc and there are usually multiple versions of each relating to a single customer. All versions of these personal identifiers need to be stored so that customers reaching you through multiple channels can be properly identified.

Next CRM systems only include a part of your customer data. Your customers browse your website, they visit specific pages, they arrive there via different forms of on-line advertising, and all this vital information needs to be included in your single customer view.

CRM systems may report sales at a company or salesman level but they don’t look at longer term customer value, or how different channels and different customer recruitment propositions bring different types of customers with different kinds of customer needs.

CRM systems may undertake bulk email campaigns, but these are not usually synchronised with other channels such as post or SMS; also given that they don’t generate any added value customer knowledge such as probability of response or likelihood of attrition, the selections they make can only be via quite simplistic filters.

CRM systems were born out of the need to enable sales forces to record their activities and results; they were not designed to ingest data from multiple online and offline sources, and deliver a complete customer view.

Over the last five years or so a new breed of technology, Customer Data Platforms or CDPs, have been developed to allow you to properly relate to customers, and to make all aspects of your marketing accountable so that for instance an online order can now be linked back to the several online and offline contacts that preceded it.

If you would like to find out why you might need a CDP as well as a CRM, please see our presentation:


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 (CDP) enhances, accelerates and democratises decision making

Using 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, and a single source of the truth, both lead 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 customer data platform help achieve all this?

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 information required to make intelligent marketing decisions 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.


Do CDPs (Customer Data Platforms) Suck?

Well, you can paint a very bad picture of them from a bean-counter’s perspective. The technology costs money, they add another item to the marketing technology stack, they have to be set up to receive data from many different sources, they then have to store all that data, and have to keep on being fed with it. Someone even has to hit a few keys for something to come out of them.

We think there is a bright side, which is not surprising to hear from people who are intrepid enough to actually build and sell CDPs.

Obviously, in themselves CDPs are worthless; the value only comes when you start to do something useful with that data. But as an enabler today’s CDPs can be something quite special.

The big picture view is that if you don’t have everything known about each customer structured and held in one place then you have no chance of meeting the customers’ expectations. And this holds true for every occasion when you are interacting with customers.

However below this Olympian vision there are a growing number of applications that are either made possible, or made to work better, when they can be powered by a customer data platform.

Here is a checklist we have made or current uses that our clients have been making of a CDP:

Outbound marketing

  • targeted and personalised direct mail
  • segmented email campaigns
  • triggered email campaigns
  • SMS push notifications

GDPR/Call center support

  • consent storage
  • privacy portal for SARs
  • customer recent activity search

Dashboards

  • customer and sales performance
  • linked to web browsing activity

Digital advertising

  • website personalisation (segmented and one-to-one)

Technical/ analytical

  • includes browsing history in the SCV
  • bespoke engineered data fields based on the SCV
  • SCV data exports for analysis

For those not entirely immersed in the jargon, what we now call a CDP we used to call a customer database, and after that a customer data warehouse, and then a single customer view. One of the differences between now and then is that in the now we expect data to come in from far more sources, and these include on-line browsing as much as off-line transactions.

Customer Data Platform timeline diagram
Customer Data Platform evolution timeline

 


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.


Tech essentials for managing personal data post GDPR

We have tried to keep this at a very high level, but we wanted to share with you our thoughts on the minimum tech you will need:

Please don’t hesitate to make contact if you need help, as we have an affordable, pre-packaged, cloud-hosted solution ready and waiting 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.


Why marketers may still need to find a ‘true’ customer data platform?

With all the power of the major CRM packages, this may sound like a stupid question; but we have had multiple clients that use CRM vendors come to us recently because they are not getting the ‘true’ customer data platform, and hence single customer view, they need.

And these clients come from very different sectors including sport, financial services, and charity.

A single customer view that isn’t ‘true’ has some unfortunate consequences.

It becomes very difficult to accurately fulfil GDPR Subject Access Requests if Mr Smith appears several times in the system. It can lead to wasteful and irritating communications such as sending two emails to the same person at the same time. It will mean that you can be treating the same person as a high value customer and as one that has become dormant. It can mean you’re submitting an existing customer to a welcome programme because they changed their email address. It makes your dashboards describing customer recruitment and attrition inaccurate, and so on and so forth.

We believe that the problem has arisen for two key reasons:

  1. the simple one is that the CRMs may let different users set up the same individual multiple times on the system without warnings, unless the contacts provided are absolutely identical
  2. the more complicated one is that correctly identifying individuals is in fact far from simple.

So, you may have an individual with a work email and the same individual with personal email, but they share the same mobile phone number and cookie ID.

They may use a different weekend and weekday name and address, but the same email. Or they may have several devices, hence cookie IDs, but a single email address. And so it goes on.

When we set about designing UniFida, our cloud-based customer data platform, we recognised that correctly identifying people is not only very important, but also very difficult.

So we decided to store as many different types of identifiers as we could. And most importantly to store the history of them, so that we never delete an identifier, unless of course someone is exercising their right to be forgotten.

It does mean that our system has to do a lot more work when new data arrives, because it has to look at all possible identifiers belonging to all personal records before deciding where to place new information.

And that can have interesting results. As well as bringing in new identifiers to an existing record, perhaps a new cookie ID, it can in some cases link together two people whom the system had been previously keeping separate. For instance two different email addresses can be found to have the same mobile phone number, and belong to the same person.

We call the process Purning, because we create a permanent URN, or unique reference number, for each individual, and that stays the same, even if over time all their identifiers may have changed.

As long as we can link a new identifier to an existing one, we know where to put the data that accompanies it.

Anthony and Julian of UniFida

Meet two of our team, Anthony and Julian, demonstrating UniFida.

Contact us if you are interested in a no-obligation chat about how we can help 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.


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 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.

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?

‘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.

To find out a little more about Unifida please contact us. It may make complying with GDPR a little bit more possible.