AIME Tracker Launched at CX Summit, London, Oct 15th & 16th 2014

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Steve Messenger, Robert Whiteford and former Office Deport Business Insights Manager, Tony Dobbs, launched the RedRoute AIME Tracker service at the CX Summit in London on Oct 15th and 16th 2014.

AIME stands for Analysis and Improvement of Marketing Effectiveness and the AIME Tracker measures the most important brand metric you have never heard of – Effective Net Preference (ENP). This measure is predictive of future brand sales, customer loyalty, willingness to recommend and (hence also) future underlying average NPS performance.

Based on more than 15 years of analysis of combined market research and customer level transactional data – in sectors ranging from supermarket shopping to supersonic travel – the RedRoute ENP model of customer preference and loyalty is both very robust and extremely valuable.

Our launch presentation, which includes case study examples from supermarkets, office supplies, DIY home improvement, and telecoms, is available from the conference organisers via this web link or from the “Treasures” section of our corporate web site (it’s free to register and then simply view online by going to the “Free Stuff” tab and clicking on “AIME Tracker Launch Presentation”.

You can also read our AIME Tracker White Paper by clicking this link:

The AIME Tracker was very well received by the audience at the CX Summit with many delegates requesting further information because it is entirely consistent with the NPS approach and, like the NPS method, can be easily and cost-effectively deployed whilst providing maximum leverage. Moreover it can use data from any source or combination of sources: conventional surveys, Tweets and Social Media posts, call centre interactions, and customer emails. It provides the best, most well-structured and most comprehensive review of decision-maker opinion, compiled in a way that predicts actual future behaviour most reliably.

To find out some more about the methodology behind the service you can also view this training video at

If you are interested to know how it could be used in your own business then contact us either by phone or email.

Our contact details are here:

Strategic Brand Management

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You may have seen that a new book on creating strategic brand engagement, by author John Fisher, was reviewed in the April 2014 edition of Marketing magazine.

The three key things that will determine your success, which reviewer Peter Filton of the Walt Disney Company said were in the new book, were:

- What you deliver
– How you communicate it
– What people think of you at the end

All so very true!

Elements of achieving this, as the reviewer highlighted, included things such as ‘staying nimble enough to deliver in ways that make it easier for customers to buy from you’ and to illustrate this he quoted an example of launching the Disney Channel in Germany where they used an mobile simulcast app that allowed fans to watch the channel on the move and not just on the TV.

Other similar examples and aspects of each of the three principles above are also quoted and hence the book would appear to offer sound advice on good brand management practice.

One thing that strikes me in reading all this though – the degree of endorsement this all gives to RedRoute’s five driver model of marketing effectiveness. These five drivers really epitomise many of the points made in Fisher’s book:

- Relevancy (i.e. what you deliver – and the need to “find a catalyst”)
– Identification (i.e. your image and the need to “have consistency across your brand”)
– Accessibility (i.e. “make it easy for the customer to use you”)
– Value (i.e. “if you offer equal value, it is their heart that makes the decision”)
– Confidence (i.e. “deliver what you promise – it determines what people think of you later”)

In fact, the book could be re-written as a case study in why the RedRoute ENP model is the best way to maximise the effectiveness of your marketing budget.

To find out more about the RedRoute ENP (Effective Net Preference) model, just click this link to visit the Insights page of our web site. And buy John Fisher’s book of course!

The Big Data Debate

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One of the big assertions that have been made by people working in the social media Analytics space is that social media data can be used to predict individual purchasing behaviour.

At an intuitive level this is appealing. If my friend recommends a product then if I have the same need I will be more likely to consider that product as a solution to my need. Furthermore, I may signal that I have that need by Tweeting that I have (or indicate I am likely to have) such a need.

But from a brand owner’s perspective there is still a fundamental conceptual issue here, as well as a whole host of practical issues. The most obvious practical issue is “Which database do I use to manage the customer?”. The only set of universally-correctly linked set of data is the one that is owned by the individual themselves. Only they know the myriad of on-line identities that they have chosen for themselves.

Brand owners are very aware that whilst systems such as Facebook and Twitter have millions of users, there are still people out there (and we have to remember that on a global basis it is still the majority) who do not, even though they may be economically active in many other ways.

This leads to a second practical issue that is often glossed-over but which is a fundamental prerequisite – how can I link together data from disparate systems and know that I am linking the right data to the right individual? There are many ways it can be done but it adds time, cost and complexity – all of which undermine the very concept of achieving ‘close to real time response’.

What is more, however, these issues are common to every marketer – there are, at the end of the day, only one set of individuals (even if they may well have multiple on-line personalities). So in principle it makes no economic sense for each company to create ‘a single view of the customer’ because at best whatever they create will always only be a partial view. Each company that is trying to sell goods/services to an individual is only interested in information that influences their needs for those particular types of goods/services. The volume of data about other areas is just noise that needs to be simplified – at least in their view, that is. Yet as the social network data experts will tell you – seemingly unrelated data can be connected.

My purchase of an airline ticket may well be of Interest to the coffee shop chain that I use because they will know that at some point I will be going to the airport. So they can trigger a communication to ensure I use their outlet/brand of coffee at the terminal.

Which brings us back to my original assertion – what we are describing is a multi-dimensional view of the individual, not a “single customer view”. But generating that multi-dimensional view can only ever be done by an independent direct marketing (data) company. There are already many out there – and the strongest players will, ultimately, prove to be those like Nectar and Tesco who already have millions of individuals on their databases.

Unfortunately there will be many discussions ahead about data privacy, data linking, data cleaning, meta measures, and many other detailed considerations and that the average marketing director will find extremely tiresome. All they want to do is get their message across to the right people, at the right time, in the right way. Nevertheless these detailed issues will have to solved / handled if the concept of the “connected world” (as trumpeted by companies such as IBM) is to become a reality in any meaningful way. Needless to say, for the best solutions to these problems we should look to companies such as Amazon as the most likely source of the innovation rather than IT manufacturers. Their views on the world are fundamentally different.

Meanwhile, back in the real world of today, what should the marketer do to achieve his/her more immediate objectives?

The first thing to do is to make sure that you partner with a good direct marketing company – and one that spans both online and offline communications. Without this you run the risk of running “silo communications” and that totally undermines the principle of a customer-centric approach.

In addition, make sure the agency has their own consumer database, one where they are bringing together data on consumers from a variety of sources, even if those sources are not necessarily complete. You do not need them to have a full picture of the consumer, just enough to cover the key dimensions. If you need advice on who to choose, please let us know.

Secondly, if you have your own internal CRM customer database then supplement it with appropriate meta-data measures (even if they are only fused or projected) taken from as wide a cross-section of sources as are relevant. For example, in the DIY sector, data on house moves is always useful, as is data on leisure activities.

Better still, although it is harder to achieve in the short term, is to become a trusted adviser. For example, if you manage an airport, do not just focus on information about your own location but become a mine of information about all airports in that region of the world. Establishing a reputation for providing accurate, authoritative, advice about a whole category will make web site attract people back time-and-again and that will, in turn, create deeper customer loyalty and greater revenues.

Thirdly, use econometric modelling at both a strategic and operational level to maximise the returns from your marketing activities.

At the operational level this means creating appropriately-extended customer propensity models from all the measures in your customer database. In particular, calculating an “Effective Net Preference” (ENP) score for each and every customer. This will give you an instant understanding not just of their likelihood to respond to your offers but also what you need to change about your offer (other than a cheaper price) to increase that likelihood and reduce their likelihood to defect.

At the strategic level, it means understanding how much money to allocate to different types of marketing activities by understanding the levels of reach and frequency they generate. This is important because online communities generate lots of seemingly actionable data but often for only very small proportions of the customer base. To know how to optimise the media mix you need to step back and look at the net reach and frequency different types of activities are able to deliver – individually and when working in concert. Econometric modelling both describes the mechanisms involved and also measures and correctly allocates their net sales effects – providing you with the ROI’s from each of the differing parts of your marketing mix.

With this framework in place you can then, overtime, improve the data sources you have, improve your customer and prospect targeting, improve your offer(s), and improve the effectiveness of your marketing communications programmes.

It is not exactly rocket science, more a methodical approach that remains consistent over time but without becoming repetitious. This are the benefits that our clients derive from using our services and if you would like to know about it then please let us know.

Changes to Society and Effective Net Preference

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The Office for National Statistics recently released new data on the structure of Britain’s 26.4 million households. It showed that 29% of households now consist of only one person. Most of those in the 16-64 age group are male. For those over 65, the gender balance is reversed.

The most common family type in 2012 is a married or civil partnered couple without dependent children, accounting for 7.6 million out of a total of 18.2 million families in the UK.

The number of unmarried couples living together has doubled over the last 20 years.

This all has implications on the way businesses structure their customer databases and the implementation of their CRM strategies. This dramatic shift in social structure has coincided with an equally dramatic shift in household purchasing behaviour, attitudes and preferences. Except it isn’t coincidental.

Now, more than ever, a business needs to understand and react to the changing attitudes and preferences of their customers caused, in part, by their changing lifestyles and social structures. It’s essential to develop an effective CRM programme to maintain engagement and preference with the business’ customer base.

The best way of doing this is to measure and track Effective Net Preference (ENP) using a customer panel.

And how do you do this? Why not ask us?

Experiential Marketing – Faith or Fact?

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In a recent research study, it was found that nearly 80% of senior marketing executives were concerned about the lack of any robust measurement of ROI for their Experiential Marketing campaigns.  Despite this concern, Experiential Marketing continues to grow both in scope and scale and, in principle, marketeers rate the value of experiential very highly – greater than conventional broadcast advertising, for example.

They know that it is the most effective medium for making their brand memorable for consumers, as well as building loyalty, encouraging recommendation and prompting an immediate impact.  But for most, this is an act of faith rather than proven by facts.

This faith has a long tradition and heritage.  Long before these techniques were re-branded as ‘Experiential Marketing’, they were used to grow brands and create business success.

In the 1930’s, Paul Ricard started to market a more refined version of France’s popular aniseed based spirit, pastis, in the bars of Marseilles.  He did it by visiting each bar and appointing a ‘brand ambassador’ in each one, giving him an allowance to buy rounds of the Ricard brand for all his friends in the bar.  On a strict ROI basis, the cost of doing this could never be justified by the increased sales in generated in each bar, but it did start the process of creating a successful brand.

This belief that spirits brands are created and grown by on-trade experiential type activities became part of the marketing genetics of his business.  It was an act of faith.  Ricard became the most ubiquitous spirits brand in France, overtaking its older rival, Pernod and leading to the acquisition of Pernod to create what is now known as Pernod-Ricard, the second largest spirits company in the world..  These techniques helped drive the Chivas Regal brand to its position as the leading premium scotch in the Far East.  And it was all an act of faith.

But now there are relatively simple techniques that can measure the real ROI generated by Experiential Campaigns using the concept of “Effective Net Preference” (ENP).

ENP is a simplification of the general usage and attitude surveys that are regularly used to check attitudes towards brands.  Typically, such studies ask consumers to rate brands against two to three dozen attitude statements, but in reality these can be grouped together into five key drivers of consumer preference:


Relevancy                Do I need it?  Does this brand fit my needs?

Identification         Do I want to be associated with it?  Is this a brand I would be proud to be associated with?

Accessibility           What’s the time, effort and cost involved?  Can I easily buy and use this brand if I want to?

Value                         Is the benefit I’ll get worth the effort and cost?  Is this brand good value for money?

Confidence              What are the chances I’ll be disappointed?  If I bought this brand, am I sure that I will be completely satisfied?


These can then be used to calculate the ENP score for the brand.  This score is not just a number for the sake of it.  It’s important because there is a well-researched and proven relationship between ENP score and brand market share – the higher the ENP score, the higher the resultant market share.

If you measure the ENP score before and after the experiential event, the results will look something like this:


The positive shift in ENP can be directly correlated to an increase in market share.  What started out as an act of faith can now be justified by the numbers.