Category Archives: Data Insight

Data … big data? Or back to the Dark Ages

Back in the 80s, there was this thing called “junk mail”.  And it was so called because it involved blanket mailing a mass market with little or no targeting. In other words, the message was irrelevant to a huge proportion of the recipients, so just got thrown in the bin.

Then we discovered targeting, analysis, insight and profiling.  And the direct mail messages become more appropriate, relevant, cost effective, and considerably less irritating to the consumer.  A classic case of less was more.

I remember the day that “personalised laser text” became available, and we were able to send out mailings with personally addressed letters which referenced the prospect’s other interests.  Letters that said (something along the lines of)

Dear Mrs Bloggs,

Because of your interest in the world’s wild places, we wanted to introduce you to our our brand new books which demonstrate the extraordinary and dramatic nature of our own planet earthfrom volcanoes to earthquakes …. 

The letter, including that simple piece of “personal” text, was enclosed into a small envelope with a miniscule brochure and mailed out.  It achieved over three times the response of the standard pre-printed control direct mail letter which was mailed in large envelope with enormous, heavy, expensive brochure

But now the European Union is proposing to take us back to the Dark Ages and the days of blanket mailings.  Their new proposed legislation is currently in progress, and will impact every level of prospect marketing.

It’s quite clear that the increasing use of new technology makes revisions to current data law essential, particularly given consumer concern over privacy which has not helped by our own government’s appallingly cavalier behaviour and carelessness with our personal data.  (Some of the breaches committed by government departments would have, if committed by the data industry, have caused severe punitive measures.  Somehow when it’s the government which gets it wrong, the whole thing just quietly gets swept under the carpet. Rant over…)

However, in addition to technological and social media impact, the traditional media channels will suffer significant difficulties.

A brief summary of the key areas is listed below:

  1. Explicit consent to be granted by the recipient prior to any direct marketing – either by word or by action.  In practice this means that where consent is required, organisations must ask for permission to process data.  Without such explicit permission, marketing prospects will not be allowed to receive mailings or cold telemarketing calls.  Current legislation allows such mailings and / or calls to be made unless the prospect has actively opted out.
  2. The customer has the “right to be forgotten” – ie they can insist that their details are emoved from a database in their entirety.  This is entirely impractical.  Once deleted, when or if that customer appears again on the database (if, for example, rented from a third party list, or in the event that the customer makes another purchase), the customer’s request for deletion will have vanished.  So in practice, the “right to be forgotten” should trigger the inclusion of that customer into a ”suppression” or “do not mail” file so that there is no inappropriate future contact.
  3. Profiling or segmentation may not take place without consent.  This will have serious impact on those data businesses which hold shared transactional data from multiple companies, or geo-demographic data, or indeed simply work with marketing profiling models.
  4. List broking is likely to require significant changes to comply with new legislation.
  5. The definition of personal data has been extended to include, potentially, IP addresses and some cookies.  Quite apart from the fact that an IP address or cookie may be used by a number of individuals, this will make it much more difficult for businesses to analyse and profile web activity.  The impact on digital marketing will be significant and, arguably (given that there will be no ability to provide relevant, targeted marketing) counter-productive.
  6. Cost:  DMA (UK) Ltd research shows that complying with the proposed regulation could cost companies an average of £76,000 each. It estimates a total loss to UK industry of up to £47 billion in lost sales.  These costs come, in part, from:
  • Companies with 250 or more employees will need to appoint a data protection officer
  • Under current legislation, subject access requests can be charged at £10 each.  Under the proposed new legislation, this charge is to be eliminated. This is likely to result in increased numbers of requests.  In addition to the lost revenue from existing volumes of which is likely to increase the number of requests, frivolous and serious.
  • Every organisation that suffers a data security breach would have to notify Information commissioner within 24 hours
  • Right to compensation from the controller or the processor in the event of processing activity causing damage to a person
  • Increased fines / sanctions to be imposed

On the face of it, the picture looks pretty bleak.  But there’s no need to despair just yet – there is time to provide our views on required adjustment, amendment and refinement  before these proposals are ratified and become law in the UK.

But for that to happen, businesses need to act now.  There is a fantastically detailed amount of excellent information to be found at the DMA (UK) Ltd.     So have a look and check to see how the current proposals are likely to affect your business and your marketing.

Then we need to write to our MEPs – and the DMA has made this easy by providing this link which has all the vital information, including who your MEPs are.   We need to ask them to fight for the fair interests of business.

We’re all for sharing knowledge and information and enjoy a healthy debate, so if you have any questions, views, tips or knowledge, please  just “reply” below. Victoria Tuffill – victoria@tuffillverner.co.uk   01787 277742 or  07967 148398.   Feel free to visit our website.  And yes, we’re on Linked In, and Twitter

Protecting the innocent and vulnerable against First Party Fraud

Life’s not fair. And that’s a fact that we tend to learn very early on in life. But the level of unfairness generated by fraud in the UK is grotesquely unfair. The Fraud Advisory Panel states that UK Fraud is estimated to cost every adult in the country an average £765 per adult.

Against that backdrop, there is a requirement (particularly among those in the water industry, energy providers, telcos and financial services) that businesses should “treat customers fairly” – a challenging goal, given the increasing sophistication and ongoing evolution of fraud.

The many faces of fraud

Fraud has many faces – and it’s somewhere between difficult and impossible to keep up with the latest innovations from fraudsters. Fortunately technology, combined with experience, provides solutions to some of the problems. Identity verification, address and age verification, voice analysis, IP address checks, CCJ and credit checks all help in the battle against identity theft, cybercrime, password theft, credit card fraud, consumer scams and so much more. Transactional and social media all have a part to play – and can be particularly effective in the area of first party fraud.

First party fraud

So what is first party fraud? And how big a problem is it? Fraudscreen defines it as “your own customers, using their own identities, taking advantage of your inability to challenge their version of the truth, in a distance selling environment”.

And why not? It’s easy to do if you’re so inclined – just tell lies to businesses in situations where they can’t prove that you are not telling the truth.

The result? Higher costs for everyone. £765 per adult, much of which is due to first party fraud, is a huge amount of money for any individual. And it is the innocent, the vulnerable and the honest who end up paying the price for other people’s dishonesty.

Changes in culture and consumer behaviour

What’s particularly alarming is that this kind of opportunistic behaviour is continuing to grow across all demographics and throughout the UK. According to the National Fraud Authority Experian Fraud Index 2010 (April 2011), private sector fraud cost the UK economy £9.5 billion in 2010. Of this, over half was attributed to first party fraud – and when talking about automotive fraud, the percentage shot to a massive 80%!

We can make excuses about the economy, but this increase is at least in part driven by the shift in UK culture. Even in 2010, according to an ABI survey, 44% of individuals consider it acceptable to inflate the value of an insurance claim; in addition, consumers have been encouraged by the legal profession and others to claim injuries that cannot be disproved (soft tissue damage such as whiplash) – needless to say, this drives motor insurance prices ever upwards – last year saw a 39% increase!

‘Society’ has become increasingly tolerant of dishonest and opportunistic behaviour, and this acceptance has led to increases in first party fraud across home shopping, TV licensing, government-funded benefits, insurance, water and energy companies, lenders (credit cards, mortgages, banks and building societies, payday lending).

The common denominator? All these sectors offer the consumer the opportunity to receive goods, services, or money dishonestly, by exploiting weaknesses within a business’s systems and processes – particularly where there is no comeback in terms of CCJ or credit score. For example, first party fraudsters deliberately

  • Apply or place an order for goods, services, or loans with the pre-meditated intent NOT to pay
  • Tell lies on application forms
  • Claim that home shopping parcels have been returned or were never received
  • Falsify insurance claims and/or inflate the value of the claim
  • Falsely claim injuries that cannot be disproved
  • Fail to pay insurance instalments once certificate has been received

Until relatively recently, this sort of behaviour has gone largely unchallenged and has simply been attributed to bad debt, or delivery issues, or just not picked up at all.

The rule is simple. When it’s pre-meditated, it’s first party fraud.

Treating your customers fairly

The simplest solution for businesses is to tar all customers with the same brush and spread the costs among everybody. Unfortunately this means that the honest, the innocent and the vulnerable end up paying the price for the dishonest minority.

It’s hard to know that an individual “intends” to behave in a dishonest way before he has actually done so. But the good news is that, in statistical terms at least, it is possible to pull apart your customers into predictive segments of good, bad or mixed behaviour. Fraudscreen, for example, can be applied as early as prior to making an outbound marketing decision; for inbound, at point of application; even after the horse has bolted – ie when you’re at the point of collections or, worse, recoveries.

Having used conventional fraud prevention techniques to ensure you know to whom you are talking, it is then a matter of applying additional data that tells you how consumers are likely to behave. Most particularly, how they will behave in an environment where they can ‘get away with’ opportunistic behaviour – where it actually doesn’t matter what they do – because there will be no come-back in terms of credit score or litigation.

Third Party Data for First Party Fraud

There is a range of data sets that are used, individually and in combination, to prevent fraud of all types, including first party fraud.

Credit data identifies a customer’s ability to pay. CCJ and similar data is also extremely useful, but works best in combination with other data sets as it provides absolutely no information on individuals who have no CCJ against them. Geo-demographic data can also be useful as part of an overall data solution, as can transactional data like Goods Lost in Transit – a tricky area as not all GLIT is caused by bad people – it can just be that something’s genuinely gone wrong, or the person delivering is lazy or dishonest.

Consumer behaviour and attitudes

There are also data sets which can be used to understand a consumer’s behaviour and attitudes. Social data is becoming an interesting tool from a first party fraud perspective – useful insights can be carefully drawn from self-reported data on Linked In, Facebook, Twitter, Google + etc. In insurance, CUE, though it has some bugs to iron out, provides claims information which can be a useful tool to verify whether or not people are telling the truth on their application forms – especially as the consumer is now quite sophisticated in his use of aggregator sites to test which answers to which variables will provide the lowest premium. The application form has now become more about price than telling the truth.

And, of course, there’s Fraudscreen, a data solution which was designed from the outset to identify consumer groups who are likely (or not) to behave opportunistically (ie first party fraud), and provide categories of consumers who are statistically more or less likely to lie for their own gain, or steal if it’s easy, or claim money or refunds from service providers. Fraudscreen can be applied across sectors to segment customers into groups of predicted good, bad or mixed behaviour. It’s an ideal solution for helping businesses in their goal of treating customers fairly as its data provides insights into consumer attitudes towards payment and honesty. And it means that the innocent or vulnerable consumer is less likely to pay for the behaviour of the opportunistic consumer.

First party fraud isn’t going anywhere, and the issues of treating customers fairly will continue to grow. A water company recently quoted that honest consumers end up with an additional £16 on their water bill, purely to cover the costs of those who won’t pay. Rather than make everyone pay for the faults of the few, surely it would be fairer to punish the dishonest, reward the honest, be fair to the innocent, and help the vulnerable?

Fraudscreen was designed to help businesses treat consumers fairly, and succeeding in that challenge will provide businesses with a real edge over their competitors, help them gain and keep new customers, afford excellent PR opportunities and improve their profitability.

Victoria Tuffill is a direct marketing consultant with over 30 years experience. She founded Tuffill Verner Associates consultancy with Alastair Tuffill in 1996. She is also founder and Director of Fraudscreen – a data tool that assists in the prevention of 1st party fraud. Her experience ranges across businesses including publishing, home shopping, insurance, utilities, telcos and collections.

© Victoria Tuffill and Tuffill Verner Associates, April 2012. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Victoria Tuffill and Tuffill Verner Associates with appropriate and specific direction to the original content.

Big Data – a new world of consumer information

Some four years ago, I was chatting to the head of a large data company, who was complaining that he had, on average, over 80K pieces of transactional data per supermarket customer.  Taken at face value, that sounded terrific.  But his difficulty was in understanding what was significant and what was not, so that he and the client could identify and use the relevant data quickly and effectively.  As I started speaking to more businesses, I heard this theme again and again – even Debt Collection Agencies found they just had too much data and not enough time to be able to understand how to find and apply the useful key data to improve their results and ROI.

 The Three ‘V’s

Even in the few years since then, volumes of data have simply exploded – Analyst Doug Laney described it accurately as being three-dimensional – a combination of volume, velocity and variety. His terminology is now widely used.

Big Data began with consumers shopping over the internet.  Businesses started to save and analyse data from clicks, searches, registrations, purchases.  Of course, having collected the data, many companies were quite clueless about how to analyse and use it.  But those who looked further ahead, like Amazon, were able to harness its power to gain market share against their competitors.

And the situation has developed further. More recently, consumers have discovered other uses for the web and smartphones – they use social networks where they post personal and business information about themselves, they link and hold conversations with their friends, family and colleagues, they post updates and information and photographs and music and films and videos and reviews and … the sky (or should I say cloud) is the limit.  And the data they are so happy to provide is available for marketers and businesses if they’re ready to take advantage of it and can cope with its relatively unstructured nature.

Combined insight:  Big Data plus traditional data

Data has always been used extensively by consumer-facing businesses to segment and target customers.  But Big Data demands a more agile approach towards engaging customers, and providing a more personal or tailored shopping experience.  Combining Big Data with the traditional purchasing and customer data previously used by business offers a massive opportunity to gain three-dimensional insights into consumers – whether for marketing purposes, product development, or customer service and management.

Forward-looking businesses and retailers will track an individual’s behaviour, including product or offer preferences, and model – in real time – that consumer’s likely behaviour.  While the customer is shopping, the business will be able to offer appropriate upsell products, loyalty programmes and increase spend and loyalty much more effectively than any competition who fails to take advantage of the opportunity.  The retailer will know when it’s safe to offer credit and on what terms;  they’ll know what the consumer wants and will be able to choose how … or whether … to deliver those needs.

Big Data Benefits

And the benefits are not just limited to retailers.  Telcos, media companies, utilities, energy providers;  insurers and aggregator sites – Big Data allows genuine communication between provider and consumer – and the consumer is beginning to understand this, and take advantage of opportunities to “switch” providers or suppliers or retailers so that they interact with those who understand their needs and wants, and are prepared to engage with them on that basis fairly and openly.

Big Data Big Issues

As ever, Big Data has its difficulties as well as opportunities.  There are concerns about data security and data privacy.  And not least, concerns about the ability to analyse Big Data –reflected in the growing number of software firms who specialise in data management and analytics – growing at almost 10% per annum – which is roughly twice as fast as the software business as a whole.  According to McKinsey, by 2018 as many as 140,000 to 190,000 additional specialists with deep analytical skills in Big Data may be required.

And there’s a Big Data technology revolution too – Big Data will need new and different technologies to allow efficient data processing swiftly enough for the data to be deployed effectively in realtime, such as MPP (massively parallel processing) databases, the Internet, and cloud computing platforms.

So where will Big Data go from here … interesting times!  And    whether you’re a marketer, a data provider, a software business, or an insight and analytics business, those who adopt an agile, creative approach to the issue will be the overall winners.

Click here for more information on TVA’s Data services.

Victoria Tuffill is a direct marketing consultant with over 30 years experience. She founded Tuffill Verner Associates consultancy with Alastair Tuffill in 1996.  She is also founder and Director of Fraudscreen – a data tool that assists in the prevention of 1st party fraud.  Her experience ranges across businesses including publishing, home shopping, insurance, utilities, telcos and collections.

© Victoria Tuffill and Tuffill Verner Associates, April 2012. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Victoria Tuffill and Tuffill Verner Associates with appropriate and specific direction to the original content.