Five ways your data strategy can make or break your business

In the past decade, digital information has become a data avalanche. We have moved from having limited information about our customers to predicting how tweets may affect their shopping habits. We know that technology is influencing consumer buying habits, and as we approach the busy holiday shopping season, now is a good time for etailers to assess their data strategy.  

According to Gartner, the volume of intelligent data is set to grow by 800 per cent over the next five years (Source: Forbes, Big Money says It’s and Paradigm Buster, June 2012). When the correct data strategy is implemented, the tangible rewards of customer loyalty and enhanced sales can outweigh the risk of missed sales and disengaged customers. As we deal with a constantly evolving multi-channel environment, it is vital for etailers to assess their current data monitoring, including social data, and address the challenge of analysing big data.

We have now reached a point where the amount of knowledge we can gather from data is unprecedented. We know that online retailers automatically capture data with every transaction, and at a basic level, can gauge customer habits, budgets and buying patterns. This data represents valuable information. Consumers want a customised approach: they only want to see the products they might buy at the price they want to pay. Yet, it seems like this rich seam of information is not always mined correctly.

The following are five ways retailers should be using data strategy to help achieve success:

1. Know your customers

It is crucial for businesses to understand why their customers buy from them and incorporate this motivation into their messaging. Better data analysis can improve the marketing message and ultimately may lead to increased sales. Retailers who can make it easier for customers to find what they want in the least amount of clicks can improve cart conversion rates and by using data from existing customers’ shopping habits, can help to improve the site search relevance for new customers.

Eighty-four per cent of people would walk away from a company that doesn’t listen, according to Experian Marketing Services (Source: Experian, From concept to reality: achieving the Single Customer View, 2012).  Recommending products, targeting relevant promotions and helping customers navigate sites in a personalised way may enhance customers’ sense of trust in the retailer. And with repeat shoppers spending up to seven times more than first-time visitors to a site (Source: Adobe, The ROI from Marketing to Existing Online Customers, 2012), the investment can be worth the reward.

2. Data rich, information poor – a common problem

90% of the data in the world today has been created in the last two years (Source: Forbes, Improving Decision Making in the World of Big Data, March 2012). But according to a recent study by Corporate Executive Board, only 11% of retailers use data for decision making purposes. Data and knowledge are not the same thing. Many online retailers could be considered data rich but information poor.

Retailers such as Boots and Marks and Spencer are already gathering, aggregating and analysing structured and unstructured information in a highly formatted way, resulting in improved customer spending (Source: Corporate Executive Board, cited in the Guardian, Why big data means big business for online retailers, Dec. 19, 2012). To take advantage of this information, it is important to make sure that retailers act upon these insights quickly enough to influence the decision-making process of the consumer. Those who can influence the greatest change are often found close to the customer.

3. Pin down a social data strategy

Social media monitoring is now a valued source of business intelligence, and can be used to identify, predict and respond to consumer behaviour. There are a myriad of tools available which offer different ways to analyse, measure, display and create reports about your engagement efforts. Mined intelligently, social media data can provide a wealth of insight about customers’ preferences, opinions and buying habits.

According to one report, 500 billion consumer  impressions about brands, products and services are shared online annually and 78% of consumers check peer recommendations before making a buying decision.

Forward-looking retailers are using analytics in real-time to capture a sizeable share of the market by interacting with consumers more effectively, capturing consumer spend, identifying new trends and strategies and developing new operating models to ensure a more timely response to customers. There is huge potential for retailers to leverage their unstructured social media data to create a complete history of all transactions and interactions across channels for each customer.

4. Insights from your payment data

Incorporating insights from payments data into data analysis can also help to enhance profitability, customer experience and efficiency.

Authorisation analysis, for example, can provide insight into peak and trough times of sales activity, which in turn can help improve the effectiveness of customer communications. If a customer’s peak shopping time is noon on Friday, then the marketing message needs to be timed to precede the peak and avoid the trough. Payments data can also provide insight into geo-business which can enable retailers to target potential customers by location and to consider the option of adding additional currencies. Payments data can also provide insight into the average spend by card type.

5. Are retailers ready for Big Data?

With more data than ever before, how are companies supposed to cope? Where should the knowledge, manpower and skills to manage this data come from?  In the UK, 75% of organisations are currently investing in Big Data analytics, and in the past six months, big data analytics has become one of the top three IT priorities for businesses.

The good news is that companies may not need to hire teams of data analysts immediately. Many ecommerce companies may already have employees in situ who are suited to a transition to data analysis. To ensure data mining projects are successful, organisations need to assess their existing infrastructure and understand that the way in which data is stored can directly affect the company’s ability to extract meaning in real-time.

With all these steps in action, what is the impact of investment?

Research has found that companies that invested in data analytics saw a 49 per cent increase in revenue growth (Source: Monetate, from Big Data to Big Personalization, June 2013). Approximately 63% of companies said the use of information and analytics is creating competitive advantage for their organisations. Our research also has shown that companies who saw their profits increase in 2012 used data  to help shape their future multichannel sales strategy including identifying any payment challenges. The above figures highlight how a retailer’s strategic use of its own data may help it stay one step ahead of its competitors.

Shane Fitzpatrick is the president and managing director of Chase Paymentech Europe Limited.