Sarah Belsham is a data analytics specialist at RSM. In this article, Sarah shares her insights on how retailers can harness the data they already collect.
To hear more from Sarah why not check out the ICAEW Retail Community webinar she took part in recently:
There are proven business advantages to using data as a strategic asset. For retailers, these include:
- creating great customer experiences;
- improving customer retention;
- managing revenues and costs; and
- remaining competitive.
Our survey, what’s in store?, found that few retailers are making full use of their data assets. Instead, they tend to use data primarily to monitor financial performance.
Customer experience and customer retention
Data is critical to customer retention. What do customers like? What do they want? What do they need? The more information you have about your customers, the more it can benefit sales and customer retention.
Customers demand a seamless omnichannel sales experience. This means the total integration of online and in-store shopping, with the flexibility for shoppers to buy from one and collect from another. Leveraging stores as showrooms is a core part of omnichannel sales. The in-store experience can be personalised by incorporating other data.
The Met Office, for example, can provide retailers with detailed long-range weather forecasts and historical data tailored specifically by location and industry. Comparisons can be made with sales data to predict consumer needs and behaviour, and the forecast of a major adverse weather event can also be used to mitigate disruption to the supply chain and customer deliveries.
Pricing and the bottom line: Managing revenues and costs
Pressure to grow revenue and improve efficiency is increasing, even while companies must maintain cost bases. Data analytics can give insight into customers and the products they buy, at what price and how often. Underperforming companies can focus their efforts if they understand what their best sellers are, not just in terms of revenue but also profitability.
Using data analytics to calculate and report total cost to serve is an effective way of improving profitability. You can identify and eliminate non-core products and focus more on brand objectives. Don’t forget stock management; too little means missed sales, too much results in excess inventory and waste. Again, understanding your customers is key. Are they prepared to pre-order items, helping your inventory and supply chain planning?
Staying competitive
You can be sure that your competitors are collecting information about your customers in attempts to lure them away from you.
Leveraging data and analytics in real or near real time can get you ahead of their plans. Identifying changes and emerging trends in time to adjust without negative impact is the key to ‘profit-agility’. A daily view of the previous day’s best-selling products, items returned by customers, and customer feedback lets you react quickly to changing market demands.
Businesses get ahead of the competition by combining that internal view with details about regional, national, or global trends. Those that routinely and quickly course correct based on knowledge of changing customer, market, and economic conditions are likely to enjoy strong customer loyalty and keep a competitive advantage.
Starting your data journey
Remember, one size doesn’t fit all. There are many solutions available. The main thing is to have a clear goal before embarking on your data journey. Start with clear business objectives and executive sponsorship. Data analytics initiatives are most successful when they’re business led and aligned to the business’s strategic objectives. Take the time to:
- understand your data sources and the processes that create that data;
- identify up front the data needed to support your strategic objectives and, importantly, where there are gaps in that data.
Selecting the right technology and tools is important. To ensure their successful adoption, however, equal emphasis and investment must be given to non-technical aspects. This means a cultural shift, involving everyone in the organisation, developing data literacy skills, having board-level buy-in, and generating excitement about using data. And remove data silos – get people thinking about the power of working together, joining their independent data sets to create a richer and broader enterprise data platform.
When it comes to developing the solution, keep it simple and create a platform for growth. Introducing data and analytics in increments, each one delivering business value, will ensure regular and tangible return on investment, as well as allowing delivery teams to remain aligned with business requirements.
*The views expressed are the author’s and not ICAEW’s.
