Thinking

How data-led retailers get their edge (part 1)

The more experienced and sophisticated the organisation becomes, the better their tools get, but you don't have to be a big player to leverage big data, or more importantly - the right data.

The more experienced and sophisticated the organisation becomes, the better their tools get, but you don't have to be a big player to leverage big data, or more importantly - the right data. In this first blog of a series of two, we will explore how starting with your customer and being clear on what decisions you need to make, will help you build the foundation for improving your edge. 

If you had to guess how much of Amazon’s revenue is generated by their recommendation engine, what would you think? The answer is 35%*. More than a third of revenue for Amazon comes from the technological advances above, and a significant enabler is big data. All core decisions and recommendations rely on insights, and insights rely on data, so if you want to get or protect your edge, you need to understand how to increase and realise the potential of your data.

The examples to use data effectively are virtually endless; product pricing, future store locations, customer journey enhancements, when to man the cashier to increase throughput or looking at ways to monetise your data - the potential is growing, so why isn’t everyone doing it?

It is hard to get right and can be overwhelming. Google receives 3.8 million searches per minute, Youtube gets 4.5 million video views in the same one minute and 188 million emails are sent per minute. The amount of data is not only enormous, it is growing exponentially**. As a result the mental and computer-power needed to collate, sort, synthesise and assess to glean meaningful insight at scale is monumental. In addition, the relevance of this data is continually over-written, so the assessment needs to be as real-time as possible. 

It seems then, that managing big data can be overwhelming, but there are multiple tools and alternatives to help organisations create real-time insights to make better decisions. But before picking the tool, you need to understand the challenges and opportunities of your customers and business so that you can measure what matters.

Understand your customers and ask yourself which big decisions you need to make

By clarifying what decisions you need to make and what you want to improve, you identify what needs to be measured. In order to identify what to improve, start with paying customers and future prospects who engage or could be engaged. If there is little data, start with user research to create the ‘Voice of the Customer’ and a Customer Journey, or even a Service Design. This will highlight the customer touchpoints and how the firm serves the customer. For prospects, who do not have a voice yet, the prospect journey with digital touchpoints can be assessed using website or app analytics. Those assessments will reveal what data you can capture where, and either enable you to better assess the data you have or invest into extending the data you receive.

These customer insights can be complemented with qualitative research to ultimately create a 360 view of a customer. If the customer engagement is purely digital, this creates an even larger data set that can be presented in real-time, enabling location-based marketing, accurate product recommendations or journey enhancements opportunities. 

Other tools such as Natural Language Processing and its application via sentiment analysis provide insight into how a brand is perceived on social media, while the data you already have reveals who your customers are, how they behave and what they need. All these details ultimately enable leading companies to understand their customers and refine the experience they provide at a personal level in real-time. This in turn reveals how to target customers with what and when - improving the chances of increasing engagement and highlighting what should be measured.

John Lewis has used this within their Business Intelligence Unit to capture data points throughout the customer lifecycle to understand what customers really want and how they behave. As a result, they were able to optimise the experience and proposition consistently and effectively.

Go beyond the foundation of your data strategy

By understanding your customers and the potential of their data, firms have the key to unlock improved customer experience and business performance. Once this is established, and the overall approach is agreed in principle, you can ask yourself these four questions to realise the potential you unlocked:

  1. What data analysis to do yourself and what to get help with
  2. How to optimise the business to serve customers end-to-end 
  3. How to find, generate and target the best customers
  4. How to build a resilient and sustainable business that will stand the test of time

In our next blog we will explore these four strategic considerations in more detail and outline  how data-led retailers not only get their edge, but retain it.

 

 

*https://zoolatech.com/blog/how-big-data-analytics-change-the-retail-sector-right-now/

**https://insidebigdata.com/2017/02/16/the-exponential-growth-of-data/