Make certain that your retail proposition sticks

Understanding the actions of the customer including their eventual decision to buy – or not – sits at the heart of what differentiates an effective growth organisation from one that isn't. Building this insight, and then using it to drive growth across every channel, can create a significant and disproportionate advantage for your retail business.

There are some obvious differences between purchasing online and buying in a bricks and mortar store, but our research concluded that whilst shopping behaviour might change – for example shopping for longer online before deciding to purchase – what customers are looking for in making that purchase does not change. In other words, regardless of channel, the same customer is looking to make their decision against the same buying criteria.

This understanding has opened up the opportunity for businesses with multiple routes to market to exploit their online channels not just for driving sales but also for building insight into customer buying criteria in their market: what we call 'triggers to purchase'. Even more importantly this provides business with the opportunity to add to its data sources. Until recently, the best source of predictive customer behaviour data was mining historic purchase information and using this to predict future purchasing interest. Alongside this, business leaders can now access 'real-time' data gathered at point of purchase, not just about customers who have 'bought' but just as importantly about people who have viewed but chosen not to buy.

However, what differentiates the most successful businesses from their competitors is not just their ability to create the right data sets and mine them for relevant information but how they go about using that information to understand customer behaviour and identify the optimal proposition that encourages more people to purchase. What sits at the heart of successful digital businesses is the ability not just to build great insight but to design and test for the most effective response.

Test and learn

The opportunity to track customer outcomes, understand the reasons behind them and then act with far greater certainty than is offered by traditional market research comes from two aspects that are unique to the online world:

Testing online offers a far greater certainty to business leaders in assessing marketing communications, pricing points, sales propositions and product appetite than the testing strategies available to date, as it can provide a simultaneous comparison between competing options in the same market at the same time under exactly the same conditions.

Because it is based on an understanding of probability, utilised intelligently, online analytics can provide business leaders with significant data samples that can very quickly (and cost-effectively) provide the insight from which strong hypotheses can be developed about customer behaviour. It can also unleash the potential for improved performance through changes to communication of the proposition, or to the proposition itself.

Our approach to online analytics provides qualitative as well as quantitative data. It applies the traditional scientific methodology to address hypotheses: test and learn in controlled conditions. This looks for tests to prove the outcome and, only when the outcome is replicated consistently, take action. Online technology now gives businesses the opportunity to test and learn by enabling them to take a proportion of their customer traffic through a different presentation (revised sales copy, revised headlines, revised 'call to action' etc) or even a different proposition and judge the outcome. This is called 'split testing' and enables a virtual laboratory test to be conducted between two pages in exactly the same environment against the same competitive activity. Sufficient mass of traffic through the test page gives a high probability that the result will be replicated; not just if presented to all online customers but, given the same shopper and same trigger findings, also to every customer regardless of channel.

An advantage of these test results over traditional market research is that they gain insights from all customers in the market who 'visit' a proposition, not just those who buy from them. This offers the business in-depth understanding of why customers choose to buy competing products and services, what triggers to purchase they satisfy and whether this creates opportunities for growth.

Deep data not just big data

The implication for growth is exciting: by understanding why people are buying your product online, and optimising the proposition through a test-and-learn strategy, you will reduce the number of people who currently 'fail' to buy and be able to market and invest more to acquire additional customers.

However, there is one significant assumption: that your organisation has the capability to develop powerful hypotheses about customers in your market. We have long argued that businesses have failed to appreciate the difference between a hypothesis and a thesis. The classic definition of a thesis is that it is a theory that is put forward as a premise to be maintained or proved whilst a hypothesis is a proposed explanation made on the basis of limited evidence as a starting point for further investigation. Much of what is proposed in businesses about customers is a hypothesis communicated as a thesis with supporting 'proofs' on which leaders are asked to act. The problem with this is that a thesis by definition is an argument based on proof. It should be able to be acted upon with some degree of confidence. If you present a hypothesis in this way, the business may act confidently on limited evidence. Taking decisions in this way significantly increases the risk of failure to achieve the desired outcome.

Quite simply, if you act confidently (and often expensively) on limited evidence you are more likely to destroy value than create it.

A process that generates deep understanding and then tests alternative responses to it to identify the most successful is far more likely to generate success. At this stage you have proof against which you can invest with confidence. Hypotheses are built in the digital channel through blending four sources of customer data and finding the crossover points where they combine some or all to suggest customer behaviour trends.

Broadly speaking this data comes from four types of tool applied in a way that asserts the primacy of the customer:

Next month we explore where money wasted online and will set out a framework for a more informed approach to marketing spend that is constructed on proven assumptions, clear goals and tested expertise.

This is the third extract from Leading Digital Strategy, a comprehensive book on the challenges of digital leadership, written by Professor Chris Bones and James Hammersley. Over the coming months, Essential Retail will be reflecting on the main themes from the publication, via a series of articles written by James.

Click here to read article one, 'Why are you so far behind in the digital revolution?

Click here to read article two, 'Customers are key to your growth: just ask them'