Thinking

How data-led retailers get their edge (part 2)

To start the journey to get the edge, start with understanding your customers and have clarity on what decisions you need to make.

To start the journey to get the edge, start with understanding your customers and have clarity on what decisions you need to make. This will provide the context and data, but the journey to change truly starts then. In this second blog of a series of two we will explore the next big four steps that will highlight how data-led retailers can retain their edge and build resilient organisations in uncertain times.

1. Decide what you can do yourself and outsource the rest 

In our first blog, we outlined the challenges and opportunities of being data-led, and the need for data literacy. One of the first decisions to make, therefore, is what you can do yourself, and where you may need some help with powerful tools. With the potentially overwhelming nature of the analysis, there is no way around powerful analysis tools. The question for retailers is whether to invest into the tools and expertise internally, or to leverage firms such as Facebook, Amazon or Google who have done a lot of the heavy lifting. 

There are multiple tools such as Tableau, Cloudera or Power BI with an enterprise licence that can collate data and provide insights, but there are also free open source alternatives such as Cassandra, HPCC or Lumify. Even Google Analytics is free and offers Marketers insights into their customers. Based on the size, existing technology architecture, quality of existing data and the programming ability of a firm, there will be a tool that can grow with your needs. Tesco, for example, is using Hadoop to accurately predict shopping behaviour to optimise their supply chain, balancing two risks: of empty shelves, and too much inventory.

The alternative to doing it in-house is to rely on existing firms to provide the insight you require. As this is becoming increasingly complex and valuable, it is no surprise that overall revenue from big data and analytics firms is expected to increase from $122 bn in 2015 to $274.3 bn in 2022. For example, Amazon is providing sellers with powerful analytics tools to better understand and reach their customers. Facebook can help find, target and influence a specific type of customer and measure the effectiveness of your campaigns.

These tools can be very powerful in helping you understand, reach and engage your customers - especially when used in combination. Once you have decided on the tools and your approach you can then reach customers more effectively - bearing in mind that with big data, comes big responsibility. 

2. Serve end-to-end, and optimise internally too

The enhancements for the customer experience lifecycle don’t stop at the line of interaction or line of visibility. By having a view of your Service Design, you will also be able to understand how back office processes can significantly improve customer experience. Big data can be used to build resilience in your supply chain, the consequence of not getting it right can mean that a country runs out of toilet paper when it needs it most, or that you have too much product that goes to waste. Delivering to customers  quickly and reliably will build trust and loyalty, while the failure will do the opposite. 

By understanding dependencies, timings and the schedule, the supply chain can be refined for Just-In-Time delivery to reduce waste and increase agility to respond to changing demands. This allows retailers to optimise their resource allocation, and increase profitability. The outcome then becomes a leaner, more agile organisation that is customer focused and relevant. 

3. Target your prospect customers or create them

When looking to increase your revenue you can either up/cross sell your offering with existing customers, or provide your offering to prospects who don't yet know that they need it. By using the 360 view of your customer more personalised recommendations can be made, market basket analysis can reveal what other customers purchased, and in-feed advertisements across platforms can plant the seeds you need to close a sale. 

The power of big data does not stop there, though. Online application assessments and in-store sensors can monitor the effectiveness of in-store and online marketing campaigns in order to refine their effectiveness - or even inform the layout of a website or physical store. Further promotions, personalised messages and tailored campaigns can then be tweaked to increase the chance of making a sale. 

The outcome is that these retailers stay at the customers’ front of mind, while building a loyal and engaged customer base that is delighted by the ever-improving and personalised experience. 

4. Build for tomorrow

One of the most significant advantages of big data is how it enables predictive analytics and forecasting. There are two key scenarios showing how leading firms utilise this. First, by serving products and services ahead of the trend, companies can reap the first mover advantage while continually innovating their offering. Being innovative in the product development cycle and delivering quality products faster than the competition increases the chance of a successful sale, while improving customer experience.

The second application is in the design of the retailer and the strategic decisions it needs to make. Retailers that stay relevant need to evolve, and insights from today enable better decision making for tomorrow, giving businesses enough time to adapt for the future. 

Crucially, retailers that retain their edge optimise today, while future-proofing their business. Big data enables the insights which lead to better decision and customer engagement. The beauty of big data is that you don’t have to be big to use it. The five stages above in your data journey are company size agnostic; the key is clarity in the decisions that need to be made and the method in which you glean the data - and the data will keep on coming, you just need to use it wisely and ethically.