conversation about maximising value from customer insight

Poll: Which breed of CI leader are you?

Colourful BullIf you watch the actions and listen to the language used by most CEOs, especially where they choose to focus their time, you can often guess their background. What I mean is their functional leadership background, whether that be finance, marketing, operations, sales, etc. This, of course, is only natural and probably reveals their area of greatest interest or where they feel most comfortable. As a leader we can all have the tendency to spend a little too much time in our comfort zone or pet projects.

This got me to thinking, does such a bias affect customer insight leaders? Do leaders with a background in IT, Data or MI lead their whole team differently than those with Analytical backgrounds in Finance or Research or Marketing backgrounds? It is an interesting question and a potential blind spot for leaders.

So, I thought I’d start by gathering some data through a quick poll. Apologies if the categories don’t work for you first time, I’ll refresh this as I get more qualitative feedback…

Segmentation

photoSegmentation is one of those customer insight and marketing terms which divide opinion. Leaders have their favourite approaches. Boards can be ardent fans of the need for a segmentation, or complete unbelievers in what is perceived as marketing “spin“. One of the reasons for this appears to be, the mixed fortunes of implementing segmentations. Some companies extol real benefits, and focus that have come as a result, whilst others bemoan wasted spend with consultants and agencies.

My own experience is that appropriate segmentations can add real value and enable a clearer understanding to focus on appropriate target audiences. But a few misconceptions need to be addressed.

The chief misconception I would cite is, the belief that any company or market only needs one segmentation. One of the guiding factors for selecting the most appropriate segmentation approach is the purpose for which that model will be used. A segmentation to guide market participation strategy, is a very different challenge, to one for new proposition development, or to target different customer treatments. For this reason, it can be beneficial for a company to have more than one way of segmenting it’s customers (even if one is considered primary when seeking to embed in culture of organisation). One analogy for this is the benefit of having a Rubik’s cube set of segmentations for decision making.

It's a misconception that a company or market only needs one segmentation Click To Tweet

Once the challenge of identifying the purpose of a segmentation is overcome, using incisive questioning, then a CI leader needs to select the most appropriate tool for the job. Here there does appear to be a degree of fashion influencing choices over the years. Many years ago, simple demographic segmentations were popular and can still perform a useful function. At the height of influence from market research teams, attitudinal segmentations were favoured and are also more viable than many believe. Since the success of Dunn Humby and others, behavioural segmentations took centre stage. Directors, particularly finance directors can favour value-based segmentation and operations directors can favour simpler life stage/“needs based” segmentations.

As all these segmentations have had their day, and still have their advocates, it is not surprising to find more organisations these days with hybrid segmentations. Popular combinations for hybrids appear to be value + life stage  or behavioural/trigger + value based segmentations. Having once achieved developing a rich attitudinal segmentation, from substantial quant research and then producing predictive models to overlay this onto a data warehouse for targeting – I regret how much attitudinal segmentations are dismissed nowadays.

However, my guidance to customer insight leaders is, to be aware of as many potential approaches as possible, and then to focus your efforts on being clear as to the purpose for any one segmentation. At the end of the day, it is not a ‘universal truth’ about customers, it is just a model to enable appropriate action.

The Hybrid CI Leader

I was struck by this graphic by Visually that was trending on Twitter a couple of days ago.

the-modern-marketer-part-artist--part-scientist_5175880e42760_w540

Apart from being an eye catching infographic and ringing true as to the challenge for modern marketers, it prompts an equal or bigger challenge for insight leaders. Over the years this role has evolved into one requiring CI leaders to have an even more hybrid mix of talents than their marketing peers.

I’d be interested to hear your views, but from my experience I’d say the ideal Customer Insight leader is a hybrid of:

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Book Review: Time to Think by Nancy Kline

Time to ThinkDo you have time to think in your leadership role?

I first read this book over a decade ago, but it made such an impact that I have kept coming back to it over the years.

It is not specifically about customer insight, although it’s implications for how to create a ‘thinking environment’ should be of interest to researchers and those designing customer experiences. However, for me the biggest lessons from this book are for leaders (including customer insight leaders).

As you read through the initial chapters on the ten components of a thinking environment, it’s easy to be struck with how different these are to the typical corporate working environment. Giving colleagues time to think for themselves, use of appropriate incisive questioning to help them problem solve and giving regular appreciation can all feel very alien from being ‘part of the machine’. (more…)

Poll: Follow-up to Org Design Post (your experience)

As a follow-up to my latest post on customer insight team structures, here’s a quick poll to gauge the popularity of different models.

Please answer the question below and I’ll share results and reflections once I have sufficient volume.

Has CI yet found the best org design?

Org DesignIt may seem like one of the curses of modern corporations but org design and regular reorganizations are now a fact of business life. I’m sure as an insight leader you will have seen your fair share.

As you’ve risen up the hierarchy you’ve probably changed in your role with regard to these events; from recipient to author. If you haven’t experienced this then I would encourage you to seek to be an author of such change.

From my experience two major opportunities exist for customer insight functions in this regard.

The first is to bring together the different technical areas who can best collaborate to provide deeper and more actionable insights. These include teams that are often located in different functional “silos”.

In line with my definition of Customer Insight, I would recommend bringing together: Customer Data, Analysis & Modelling, Research and Database Marketing teams. Suitably integrated and with an outcome focussed culture, these teams can together for an ‘Insight Engine‘ that produces not just technical output but actions that result in both commercial impact and improved customer experiences. (more…)

Are your customers thinking fast and slow? Irrational advice

Thinking Fast and SlowIt hardly feels like I need to write a review on this book, as I often hear to recommended at conferences. However, chatting to a few peers in customer insight leadership roles, I realise that many of you have still not read this classic or have stalled part way through reading. So, I hope this helps motivate you.

The first point to admit is this is not as easy a read on Behavioural Economics (BE) as more approachable writing styles like “Nudge” by Richard Thaler. You do get used to the style through the book but there are a couple of things that make it harder for the business reader, the depth of theory that is covered and the amount of case studies (which provider an insiders view of challenging accepted wisdom within academia). I also found that after having read ‘Nudge’ I was initially a little frustrated that this book is not structured around a simple list of biases. It appears to be deliberate as Daniel Kahneman wants you to understand the principles not just pick up some buzzwords.

That said, this is well worth reading. From the initial explanation of System 1 and System 2, through the evidence provided on multiple biases, to how poorly basic statistics and logic are applied in our decision making; this book has much to share. The deliberately more narrative style of the book also does reward the persistent reader, as you begin to see how models and principles interact and build on each other (like loss aversion and framing).

The other advice I would give if that this is a good guide to the pitfalls to beware of when making decisions or seeking to influence key decisions in your company. In that regard it goes much wider than just a textbook on Behavioural Economics. For instance the evidence Daniel shows of a failure to regress to the mean in forecasting is often beyond the scope of popular BE but very relevant.

I would recommend any Customer Insight leader to read this work. This is particularly important for those working within Financial Services, where your regulator requires consideration of how consumers really make decisions and where your research team can help your analysts with interpretation.