helping you master customer insight leadership

How to create a culture of action in your Customer Insight team

culture of action

Whilst debating the relative merits of different metrics, I’ve been reminded of the importance of a culture of action within teams.

That debate was sparked by my recent post, encouraging those implementing Customer Effort Score programmes to learn the lessons of what happened with NPS (i.e. don’t waste time arguing over metrics). Ironically this then prompted comments debating the relative merits of NPS, CES or CSat as metrics.

But it’s always good to get comments and debate going, so I’ve enjoyed the ensuing conversation here and on Customer Think blog. Whilst debating there, on the relative importance of metrics versus action, I’ve been reminded of the importance of creating a customer insight team culture which drives action.

Over a decade of creating and leading insight teams has taught me that two aspects of team culture are critical for customer insight teams to make a real difference to the wider business.

One is collaboration between the different technical discipline (to deliver holistic customer insights), the other is action-orientation, galvanizing the team behind a vision of driving change in the real world. This goes beyond delivery of technical analysis or Powerpoint, to focus on the decision & action needed to deliver commercial results and improved experiences as judged by your customers. (more…)

Poll: What’s your biggest barrier?

WallFor a previous poll, in answer to the question “which support service would you choose?”, your most popular choice was training for customer insight teams. The joint next choices were, a capability health check, or bespoke consultancy. This is coupled with 88% of you confirming that in an “ideal world” you would seek external help.

Since May, I’ve spoken at five different customer insight related conferences, and  the questions asked during these events have supported this view, that recruitment and training of customer insight analysts are top concerns. No wonder that Laughlin Consultancy, like others has developed training material to educate new analysts and those who have technical skills but no background in customer insight. I’m sure that will be a growing market as the search for analytics talent draws from a wider diversity of backgrounds.

Now, to digger deeper as to the needs of customer insight leaders and their teams, let’s focus on one of the problems they face. From talking to many different leaders over the years, at some point in the conversation most will express a challenge or barrier they face; in either driving real value from insight or realising the full value potential of their team’s work.

So, please let us know which of the choices below you would identify as the biggest barrier to realising the full value potential from your customer insight capability. This is an anonymous survey, so please share the biggest barrier you face

 

Once this poll has significant results, I’ll share ideas and experience relevant to the top challenges you are facing (as well as the results). Thanks.

CDOs, Data Sharing Standard and LinkedIn

To compliment our recent emphasis on analytics, here are a number of data related articles from other bloggers to share with you. First, in an article published within Autumn 2014 edition of DataIQ Magazine, I caution the new cohort of more senior Customer Insight Leaders to not overlook their data teams. I would recommend anyone in this role read: “Don’t turn your data team into Cinderella“.

To introduce “How can you influence at the Top Table”, I mentioned the growing number of Customer Insight Directors or  Chief Knowledge Officers now emerging as C-Suite level roles in blue chip companies. We have also shared six tips for those with the new role of Chief Analytics Officer (or as some companies prefer Chief Customer Science Officer). To compliment that content, here is an interesting perspective from IBM, introducing the Chief Data Officer role. CDOs may have a less glamorous job in many organisations, but they are no less vital to the success of Customer Insight capabilities:

The topic of data sharing and open disclosure with customers or citizens has been in and out of the news in recent years. Two communications on this topic struck me recently. The first is Tim Davies’ overview of the changes being proposed for government to register its data sharing arrangements. In light of the coming General Data Protection Regulation from the EU, this is an interesting approach which businesses would do well to watch:

On a more personal note, I had the unusual experience of being impressed by an email on how a business will use my personal data, or a privacy notice. Communications on this topic are normally so dry that they appear to be using boredom as a means of avoiding customers engaging and understanding impact. However, a noble exception recently was this email which I received from LinkedIn. Both the language used and the ethos of the approach were refreshing, perhaps other businesses could learn from this approach:

LinkedIn data notice

I hope all that data-related content helps redress the balance. It must be time for research again soon! In the meantime, do let us have your comments on these or any related data topics that matter to you.

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 MoneySuperMarket.com. 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. (more…)

How can you better influence your top table C-Suite team?

top table

As more Customer Insight leaders rise in seniority within blue chip companies, do they have the skills to influence at the top table?

This 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.

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 a regular appointment at the top table, what should you do?

(more…)