Focus on Data

Kantar, who deals in consumer knowledge and insights, wrote an interesting piece last year about how they can help businesses make the consumer experience better with all the benefits for customer satisfaction that come from it.

What was interesting was the work devoted to data collection, the application of advanced techniques to make sense of it and how what was learnt was then applied in the workplace to make a difference. Perhaps retailers, cash management companies and the cash industry have much to learn if cash is to continue to compete as a payment option.

Kantar describes how combining store-level transaction data and customer experience survey data allows retailers to understand ‘basket size’, preferred payment options and to optimise check outs so that people don’t face delays – 70% of people say the speed and convenience of the checkout experience is the most important determinant of their perception of a shop.

With more checkout options retailers need to reconcile and validate transactions better. Anomaly detection algorithms can be used to isolate suspect transactions and identify fraud. This needs good analytics and the presentation of the findings on dashboards that are easy to understand at the point-of-sale. It also allows real-time forecasting and more effective promotion strategies.

Behavioural information, customer profiling and product features are part of this analysis to identify markers that reveal and record customer loyalty, product preferences and which allow forecasts of their future purchases.

In Kantar’s case study their US retailer took card payments for 60% of sales. The aim was to reduce card processing times by 6-10 seconds because this saw an increase in customer satisfaction of 600 basis points. When machine learning was applied to upsell according to the customer’s profile, acceptance of the offer rose from 4% to 21%.

So what? To keep cash relevant and competitive, access to and an understanding of this sort of data would allow the banknote industry from producer to cash management company to work more effectively to make cash better. Payment and data analytics, qualitative and quantitative, is being collected and used but how well is cash understood? Do we know where it works well or where it needs to be better? Do we know where it creates friction at the checkout? Can we fill gaps in our knowledge so that we can help retailers accept cash because it increases their bottom line?

Data is an opportunity. We don’t want cash to get left behind.