This article builds on the argument made in my two previous articles that data analytics, and especially the emerging capability to perform predictive analytics, offer retailers a genuine opportunity to reinvent themselves as customer-centric organisations, deepening customer loyalty and enhancing profitability in a volatile marketplace.
As always, though, nirvana isn't reached in a day, and there are numerous pitfalls along the way. In this final article, I want to look at how to successfully make the move to becoming a data-driven organisation, rather than one that relies on intuition.
Based on my experience in the industry, the following key success factors need to be integrated into the plan:
Avoid grand projects and keep an open mind. It's imperative to move away from grandiose projects led by IT, to which some corporates appear addicted. A much better approach is to focus on iterative projects led by the business that are less risky and allow the organisation to learn as it goes. This in turn means being open to changing tack as the data dictates − we have to be open to what the data is telling us, and act accordingly.
Understand data needs. It is also important to recognise that most retailers already have all or most of the data they need − don't waste time and money trying to get at the data you want (or think you want).
In line with my advice in the first point − take baby steps, survey the existing data and work with that, at least in the beginning. That said, it is vital to take the necessary steps to ensure the data to be used is clean and reliable; the old "garbage in, garbage out" mantra holds good.
Set goals − actionable insights are key. A related point is that it is easy to fall in love with the data and embark on data-related projects that are interesting but that don't deliver any real benefits. A disciplined approach is vital, and a data project must be aimed at generating insights that are actionable.
Knowing everything there is to know about a customer segment for itself is ultimately counter-productive. A better approach is to identify what information is needed to reach a strategic goal or make a better decision.
A disciplined approach is vital, and a data project must be aimed at generating insights that are actionable.
It may be interesting to know a customer's preferences in the abstract, but it is only valuable when aiming to leverage that knowledge in order to get the customer to buy while they are in the store or on the website. An important element is speed: the actionable insight needs to be generated rapidly so that action can be taken in real-time.
Change the corporate culture. If the retailer is going to become customer-centric, just acting on insights is not enough. The whole organisation has to change its focus or predisposition − everything everybody in the company does or says must be founded on the customer.
For that to occur, a vital first step is for everybody to understand the direct link between customer-centricity and the bottom line (and thus, in turn, on benefits, job security and the rest of it). Segmenting customers in terms of their lifetime value to the company, and how much it costs to acquire and then service them, will help to make the business case for data projects. It's particularly important that the CFO is involved so the return on investment for specific data projects is well understood.
Another central part of the new culture is a shift towards making decisions based on evidence only, not on emotion.
Use the growing understanding of the customer intelligently. My main point here is to ensure the customer experience is well designed in light of this knowledge and is constantly being refined via a feedback loop that links into strategy and operations. Every interaction with the customer, including those undertaken by software, must be linked to data.
Leadership must be on board. A profound change like this will not succeed without strong leadership. It is a vital step to get the leadership team on board and motivated.
Pay due attention to talent management. The customer-centric retailer needs staff who have the right skills. Specifically, this means access to specialists like data scientists but generally an ability to solve problems and follow logic becomes critical.
Make sure the technology is in place. As should be clear by now, technology is not a silver bullet, but it does need to be in place. Storing, processing and analysing fantastically large amounts of data depends on technology, and the building blocks must be solid.
Develop a pilot to demonstrate the value of predictive analytics to the organisation. There's nothing quite so powerful as a successful project. It remains important to make the case for data's role in helping the company to become more customer-centric and why that would be beneficial but give the project the best chance of succeeding by carefully designing a pilot project that can be relatively quickly deployed to show what you mean.
Retailers face a set of tough challenges in the short- to medium-term. Only those that harness the power of data to help them understand the challenge and craft effective responses will survive − as will those that understand this is not a quick dash, but a journey undertaken with an open mind.
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