“What we need is a single view of our customers, a 360 degree, all encompassing, de-duplicated perspective. One that aligns the digital world with our bricks and mortar reality in the ever changing…”

This is a common conversation, one I’ve had with countless professionals from a variety of organisations. It is not unique to any one sector or discipline.

It’s the ever present challenge to rationalise countless customer touchpoints; emails, comments, purchases, clicks, scrolls, conversations and much more, into something coherent and comprehensive. The ability to capture data from every possible pipeline and refine this to singular insights about your customers.

I’ve previously talked about difference between data and information; that the former is a raw material whilst the latter a refined commodity forged in the crucible that is analytics. The emergence of big data and, later, deep learning as everyday processes is a testament to the sheer volume of data out there and our need to streamline the process by which we derive insights.

Deep Learning is fantastic for the ‘let’s throw all this in a blender and see what comes out’ approach to analytics, and this definitely has value in understanding large scale trends across enormous data sets from a macro perspective. If, for instance, I want to understand the shift in dining trends for the whole of London over the past 5 years based on trip advisor, yelp and twitter hashtags, this is a large scale pattern and well suited to deep learning.

However, if I want to understand what one of my customers is interested in, the waters get a little murkier. On the face of it, this seems a simple problem – just query all the stores with the relevant data in and build a singular perspective, right?

Well, not quite. A widespread problem with this hypothesis is the age-old question of data quality and master data management; how can you be sure the data you have is accurate? What if Miss Joan Smith of 36 Invention Street has moved? What if she has a new phone number? What if she has decided to change her name?

You may have the answer to these questions, just not in one place. The most recent phone number may be captured in your CRM but with no address data, whereas the current address is held somewhere else. What if you have another address held in another system but with different door numbers – they both validate but how do you know which is the correct one? How do you build a consensus about what is valid and what is not?

In my experience, MDM (Master Data Management) and DQ (Data Quality) projects are famously difficult to implement due to a simple maxim; how do we know what is true? Without getting this right it is effectively impossible to get a single view of any customer with confidence.

Now let’s thrown another factor into the mix – GDPR.

As I’m sure many of the people reading this missive will know, GDPR is kind of a big deal right now. Due to be implemented in May, it has the potential to flip the sales and marketing world on its head, and beyond. If you aren’t familiar with this piece of legislation then I urge you to do some research – the fines are very high for non-compliance, with additional compensation potentially awarded to claimants on top of these fines being unlimited.

As part of GDPR individuals covered by the legislation have fundamental rights and principles, I’m not going to cover all of them here – that’s an article all on its own and one that has been written countless times across the blogosphere – but I do want to highlight one;

Article 5 of the GDPR requires that personal data shall be;

D) Accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that personal data that are inaccurate, having regard to the purposes for which they are processed, are erased or rectified without delay;


This changes things somewhat; inaccurate customer data now carries the potential for financial penalties to those organisations that do not address the problem. Suddenly the mismatch of addresses for our Miss Joan Smith threatens not only the bottom line, but the reputation of the company and consumer confidence.

But how do we solve this? We’ve already highlighted that MDM and DQ projects are famously difficult to get right, and whilst no one is expecting perfection from any solution of this type how do we prove that “every reasonable step has been taken”? Do we know what actions have been followed? Is our data non-compliant?

Enter blockchain. Over the past few years a number of compelling blockchain storage solutions have popped up globally –  BigChainDB is worth of note, as is  Fluree or even  MongoDB if you want something a little more established.

Now blockchain is something that has firmly embedded itself in the technological and cultural zeitgeist over the past few years. The snap growth of Bit Coin, the vast influx of new cryptocurrencies into the market and the perversion of the intended purpose (away from a replacement to everyday currency to that of another traded commodity like stocks and shares) has seen this once curious experiment explode into a worldwide phenomenon; for better or worse Pandora has definitely opened the box.

However, the facets that make cryptocurrencies possible could easily be applied to a person.

Like a bitcoin, you are truly unique. You are not just a collection of atoms, but also everything that organised structure has experienced up to this point. Even in the case of genetically identical twins, the two are distinct individuals with their own journeys, memories, and lives whose genetic code has been drifting apart ever since that one egg became two.

Bitcoin’s work in the same way, the blockchain that represents the bitcoin itself is not just the description of the collection, but every transaction that collection has been involved in to date. The irrefutable provenance of the coin, backed up by consensus, is what gives people confidence in its transactability. You can’t copy bit coins to make more money, no more than you can copy people to sell more products.

In this immutability, this secure record of what makes a customer, what has changed and who changed it is where the potential for massive gains in creating that elusive Single Customer View comes to life.

With this perspective in mind, Acrotrend are building a system. We call it Chameleon; a blockchain powered Customer Data Mastering and GDPR compliance tracking solution.

Imagine a scenario where your customer is defined not by a simple 8-digit integer key in a database, but by a blockchain that represents every touchpoint, email, transaction, amendment and activity a customer record has engaged in throughout your estate.

Imagine that this ledger is decentralised and fault tolerant, allowing all your systems to contribute to the customer record and read to verify that the individual systems copy of the customer record is verified and correct matching the central consensus. This consensus is used to tie new entities to existing records, reconciling multiple copies of a customer into a singular golden record.

Erroneous changes can be captured through the same consensus model at the heart of blockchain systems, where if one system is slightly wrong compared to all others this can be corrected automatically.

Then fold in GDPR, and Chameleon can highlight which customers are non-compliant, at risk, or indeed have different hold orders on them such as “restrict processing” prompting recommended actions to rectify the situation.

We’ll be releasing more information on this product in the run up to the GDPR enforcement date in May, and I’m happy to answer any questions in the interim.

But stepping back, and irrespective of anything else you may take away from this article, I would like to impress on you this; GDPR is only the first stage in what I believe will be a global shake up of privacy legislation as people take control of their digital assets; their information.

It’s vital that the IT profession, for which data is its oxygen, evolves to understand this new paradigm. Technologies like blockchain give confidence through their inherent design, making the digital self truly unique and secure from tampering.

Embracing blockchain in the mastering of customer records is a major step in business acknowledging the uniqueness of customer journeys, in what I believe will be part of a great public awakening in the importance of the digital self.