helping you master customer insight leadership

Event: Analytics for Insurance, Europe 2014

AFIE 2014 brochureThis conference was well attended and lived up to it’s billing of attracting insurers, consultants and suppliers from across Europe. With approximately 200 attendees and representation from over 14 different countries, it was a lively and interesting event with strong audience participation.

Six key themes emerged consistently during the day:

a) try, try & try again;

b) fail fast & fail cheaply;

c) data is an asset, manage it as such;

d) insight is more than just data or analytics;

e) cross-functional collaboration is needed;

f) measure your marketing effectiveness.

To kick us off there was a panel of speakers from leading insurers (Swiss Re, Towergate and Cooperative). Each shared how they had developed their analytics capability and seen value as a result. Some were more positive about the potential of “big data” than others, but once again the most applicable examples were using wider sources of internal data rather than social media or other unstructured external data. There were also a couple of examples throughout the day of analytics centres of excellence being created, although the best organisational fit varied. Some still saw analytics as part of IT, whilst others had established this CoE within Marketing, Actuarial or Underwriting functions. None of the organisations presenting had yet implemented a directorate of customer insight, as pioneered by some of the C-Suite customer insight leaders in the most progressive firms. However, there was good practical advice on there need for test & learn, local business understanding guiding deployment of models not IT and the relative benefits of in-housing or outsourcing your analytics capability (a question which recurred during the day).

Following this, we all had the pleasure of hearing a great presentation from Without spoiling the surprise for anyone who has not heard Orlando before, it concerned the experience Norm Larsen as a persistent inventor. Through the story of his persistence, to create a product needed for early space flight, we focussed on the cultural challenge of achieving great analytics (“it takes more than rocket science to launch a rocket”). This presentation is well worth hearing if you get the chance and landed the points (excuse the pun) of both “try, try & try again” when testing & learning with analytics, as well as “fail fast & fail cheaply” which is very relevant for those establishing innovative analytics or database marketing teams.

Several times during the day there was plenty of time for audience Q&A and I’m glad to say that at this event there was active participation. The kinds of topics the audience were raising included creating business cases for investment in an analytics team, the need for attitudinal understanding alongside behavioural analytics, how to achieve “top table” buy-in and the recruitment challenge faced by many organisations. In fact, although people accepted that graduate recruitment and talent development might be an ideal solution, the need for short term results drove the interest in outsourcing. I warned against this unless very effective knowledge transfer is implemented, consistency of personnel and planning in the time taken to become familiar with business domain and your own data. Much of my concern is of course fuelled by my past experience of outsourcing and offshoring analytics.

The focus then moved on to the use of analytics to enable more intelligent pricing. In a session that was well chaired by Celent, we heard from BGL Group, Storebrand and 1st Central Insurance. Some great geeky fun here for the more numerate. We even got an equation on a slide. Applications included credibility modelling, dynamic price optimisation and management of your street price. Given my past experience of customer insight having a key role to play in ensuring senior leadership understand the customer impact of pricing changes, I was particularly taken by comments from both BGL & 1st Central Insurance. The latter has apparently seen from analysis what I’ve experienced in the past, that unfettered optimisation will punish your most loyal/dependent customers and have decided to take an ethical stance of renewal premium rates being in line with new business. This is a huge commercial challenge for large insurers, with large back books, but given growing customer and press disquiet with the pricing differential that can emerge over years, it needs addressing. I was glad to hear other organisations using customer insight to bring to life the characteristics of customers impacted most by statistically optimal pricing.

I was also struck during the day by the level of academic background in a number of the speakers. Beyond the hype of the data scientist role, there does appear to be a real growth in analytics and customer insight (or customer science) leaders having PhDs or coming from backgrounds in academia. This certainly has benefits in the level of statistical understanding expressed by a number of speakers and it was good to benefit from some of their teaching. However, I believe there is also an inherent risk as well. A risk that predictive analytics become more theoretical and focussed on optimal techniques and thus more removed from real world customers and effectively using analytics with research and the learning of front-line colleagues in customer services etc.

Given that concern, it was reassuring in the afternoon to focus on customer analytics. I shared the stage with Christina from AIG and Marion from If Insurance (Norway). The audience appeared to respond well to my presentation and I will soon share my slides via SlideShare for those who are interested. Christina and Marion also did a good job of highlighting the range of application areas for customer analytics, including media mix effectiveness measurement and optimising your multi-channel database marketing through test and learn. The questions we received in a follow-on panel session again revealed an audience with concerns about recruiting, outsourcing and marketing effectiveness measurement.

So, another useful event to attend, and one that will hopefully help me further shape the content on this blog to address the questions/concerns of today’s customer insight leaders. If you attended this event then please share your comments below, or just let us know which of the topics raised in this post you would like to see covered in more depth.

6 key attributes of Chief Analytics Officer

6 key attributes of CAOIn this published slideshow (with associated notes), Rob O’Regan from IT World shares some sensible tips for Analytics leaders with this new job title. Chief Analytics Officer (CAO) appears to have now joined Chief Knowledge Officer and Chief Insight Officer in the pantheon of possible names, for the most senior customer insight leader in a business.

Returning to one of my soapboxes, it’s a shame that this focusses just on analytics and not the whole customer insight ecosystem. But that said, several of these points make good sense and hopefully you find them helpful. I do agree with his focus on translation, outcomes and the need to be willing to fail to learn. It is also important to embed a culture of action orientation in your team, something I’ll share more on in a future opinion piece.

Let me know what you think of this guest content.

How to better measure your Marketing Payback

Marketing PaybackBack in 2005, when this was published, I was in the right job at the right time, so as to get a free copy. However, having since read and valued this important work, I would now happily of bought copies for myself and my team.

Professor Robert Shaw is one of the early gurus of applying analytics to marketing. In this text he steps the reader through how to both make your marketing profitable and prove that ROI to the rest of your business (especially Finance).

In fact this usefully comprehensive and practical guide is equally relevant to a Marketing, Finance of Customer Insight audience. However, in my experience, Customer Insight (or Database Marketing) are best placed to bridge the gap between these two disciplines.

The book itself is divided into 3 main sections. Part 1 covers “Is Marketing profitable?”, Part 2 “Solutions to common problems” and Part 3 “Financial Planning and Control”.

The first of those sections really builds the case as to why this topic matters and frankly why you’ll want to read the rest of this book. It critically assesses the immaturity of much current marketing measurement and how the culture of some marketing departments mitigates against a more mature and accountable approach. Despite being written nearly a decade ago now, I sometime feel like nothing has changed, as I fear some marketing departments have been lured by the glitter of digital/social/mobile channels. Thus many have not carried across the kind of discipline which became the norm for direct mail effectiveness measurement. Shaw was also ahead of most thinkers in this area by highlighting both the importance of a basket of researched & analytical metrics, and the need to consider behavioural psychology biases, in your own decision making and consumer thinking.

Part 2 then focusses the reader on some of the key tools used in implementing a comprehensive framework of measurement, across the full range of marketing investments. Topics covered here include: allocating budgets to above and below the line media mixes based on optimising payback; measuring integrated campaigns; the role of price and promotions; and the more advanced stage of customer equity management. Shaw and David Merrick consider the role of brand spend (both brand changes and using a portfolio of brands to best advantage), plus more straightforward targeted direct marketing (with the complexity of integrated comms). Finally, they help you assess the adequacy of your Marketing MI, another topic I find is too often ignored in favour of reporting from Finance or Sales.

The final part of this book may seem to be more focussed at Finance professionals. It is true that there is sound advice here on planning, budgeting, accounting, and tools to use in Excel. However, this section is also beneficial for both Marketing and Customer Insight professionals to understand. From a customer insight perspective, it helps to highlight key data that needs to be captured, and once again the translation role that CI can play in meeting the needs of both Finance and Marketing (e.g. when developing evidence based marketing plans and budget allocations). Finance business partners will also find useful checklists of elements needed, from Marketing or Customer Insight, in order to reach sound assumptions and the forecasts they require.

Throughout this, now classic text, Shaw and Merrick offer practical solutions in the form of suggested processes, templates and even a few equations for key ratios. I heartily recommend this book, hopeful that Customer Insight leaders will once again ensure a focus on Marketing Payback, not just adding more channel/media complexity without first understanding profitability. As Kotler says on the cover, “A landmark book…”.

Have you benefited from applying this expertise? If so, we’d love to hear your comments.

How can you influence the top table?

influenceAs more and more Customer Insight leaders rise in influence within blue chip companies, it seems timely to consider this question. It is not just for Customer Insight Directors (CID), although that role and it’s American cousin (CKO, Chief Knowledge Officer) are appearing in more and more companies.

My last search on LinkedIn turned up nearly 50 CIDs in the UK (excluding research agencies where this job title does not have the same seniority) and over 700 CKOs in the USA. Once again, I’d expect the UK business trends to follow the US. Anyway, whether or not you have risen to the seniority of being called a CID, you are hopefully finding that your executives want to hear from you. So, when you get that call or regular appointment at the top table, what should you do?

Here are just a few tips I learnt through getting it wrong to start with: (more…)

Are Business and Sport really different?

ac-logoAt conferences and meetings, one of the topics in which you (customer insight leaders) seem particularly interested is leadership coaching. Once it’s been mentioned in a presentation, that is the most likely topic for me to be asked about in the next break. A few of the points that I’ve made on this are:

  • Coaching does work (over 90% of UK companies now use coaching and the academic evidence for efficacy has grown hugely);
  • Customer Insight Leaders would benefit as well (progressive companies are extending beyond CEO to all directors & key leaders);
  • It is for winners not losers (don’t think what’s wrong that they need a coach, think elite athletes use coaches to sustain peak performance);
  • Take care choosing a coach (a recent useful article in EDGE magazine gave a 10 point checklist of things to consider, including qualification and membership of professional body).

Given that message, I was encouraged to see a friend of mine at Abelard Consultancy also blog on what business can learn from sport, especially the importance of goal setting. So, here’s another “other”  guest content:

From my experience, customer insight leaders and other executives can really benefit from the use of goal-orientated performance coaching, to set such goals and consistently achieve them.

Event: Insurance Data & Analytics 2014

Insurance data and analyticsThis event organised by Post Magazine was pretty well attended by Insurers and their suppliers. Although the audience was pretty quiet during Q&A sessions after each speaker, there was plenty of time for questions and a good buzz of questions & ideas during the breaks. A good mix of presentations, interviews and panel sessions as well. With apologies to those who my failing memory has overlooked, here are my recollections:

Magnus Boyd a partner at law firm Hill Dickinson shared his thoughts on privacy & trust generally during an interview with our chairwoman. The most striking thing he raised was the impact on companies from the EU’s new General Data Protection Regulation. This will significantly increase the level of fines for breaches and remove the discretion to allow firms longer to declare them. It will also require larger companies to appoint a Data Protection Officer with secure tenure. He could foresee a brisker trade in insurance against data protection breaches for specialist underwriters.

I was presenting on the emerging role of Customer Insight Directors (or CKOs in the USA). Pleasingly it seems my message as to the importance of these roles, leadership, coaching and holistic customer insight complimented other presenters. You can see a part of my message in the previous post on “Breadth of Customer Insight”. A more concerned perspective might be that the majority of presenters still focused on IT, data and analytics as if they hold the answer alone. But some positive conversations in the breaks allayed my fears, at least for a number of the attendees.

Several suppliers shared what they can offer, but two stuck out for me. Visual DNA shared their work on using visual psychographic questionnaires to generate scores which they have shown are predictive of future behaviour. For instance getting customers to unconsciously reveal their risk taking appetite or conscientiousness. It was interested to see how they are using this and the volume of scores already collected. However, I do feel use of this data to drive differential pricing or cover will prompt future questions from the FCA or ICO, given the lack of transparency for the customer as to what they are revealing and for what purpose. What was encouraging was to see at least one of the suppliers engaging with the predictive power of attitudinal as well as behavioural data (i.e. research + analytics).

The other interesting company was Esri. Ostensibly a GIS and mapping data provider, I was unaware of their scale, private ownership and amount reinvested in R&D (very much like the SAS model). What was even more pleasing was to hear of their work with the UN and what a key role Esri plays in helping early on during natural disasters around the world. Providing the UN and NGOs with up to date maps for their work is a key need that does not get much media attention. So it seems that Jack Dangermond has not only built a very successful global privately owned data & analytics business, but one with CSR in its DNA. Good to see.

I was also encouraged by the final presentation from Ian Hood of RSA. He is responsible for RSA’s digital capability, keeping that up-to-date, meeting customer expectations and implementing into an omni-channel world. My encouragement came, once again, from how Ian is using attitudinal as well as behavioural data. Research was used and valued (including the valuable technique of eye tracking studies) to compliment the behavioural data on digital usage and robust “AB testing”, i.e. properly constructed database marketing to test the hypotheses reached from converging research & analysis. Right on my wavelength. It is interesting that I quite often find that this thinking and approach is more prevalent amongst digital teams in corporates, but sadly often because they are run as more independent silos from the main organisation.

So, overall a good event (and like all such events you get out what you put in). I would just like to see the brief for future such events deliberately extended to cover all of customer insight so more sharing and learning can happen across the boundaries that too often exist between data scientists and researchers.

Do you benefit from the full breadth of Customer Insight?

Customer Insight EcosystemDifferent businesses continue to use the term “Customer Insight” to mean different things.

Even in our poll of over 100 customer insight leaders, only half of you considered data management or database marketing to be part of Customer Insight. The majority also had only research reporting into them, not analytics. Does that ring true with your role?

In June, I shared a definition of Customer Insight that I find useful:

“A non-obvious understanding about your customers, which if acted upon, has the potential to change their behaviour for mutual benefit”.

I would stress 4 parts of that definition: First, that insights are non-obvious, they normally require the convergence of evidence for multiple sources to help spot themes and then dig deeper for motivations. Second, that true insights need to be actionable, as there is no point learning something unless you can change commercial results or customer experience as a result. Third, a good test of an “insight” is whether acting on it is powerful enough to change your customers’ behaviour (not just data to  target those you believe will act as they have in the past). Fourth, in this “Age of the Customer”, the importance of trust should mean any insight has the goal of mutual benefit for the organisation and the customer, anything else is short term success for long term value erosion. (more…)