An intelligent use of customer data will facilitate retention and protect the health of wholesale operations, says David Gilroy
Wholesalers depend on driving customer numbers: either acquiring new or maintaining existing. We all know how difficult it is to recruit new customers in the sector but I remain to be convinced of the value of sales people in the process. They are expensive and their return on investment is questionable.
Keeping tabs on them and making them accountable is a big challenge (read nightmare) albeit easier now with tracking technology. I’ve always looked for more efficient ways to acquire customers and too often sales people morph into quasi-account managers building relationships taking orders, keeping customers happy, collecting debt and moving stock around. Doing anything other than landing new business. Now that Covid-19 has all but put paid to face-to face selling the switch to customer retention should be intensified.
Wholesalers are sitting on a goldmine of rich customer information, which they have been accumulating for years. But how many are actively managing and measuring the data to continually assess the health of their businesses? Time and resource spent interrogating the customer files will bear far more fruit than deploying an expensive sales force. A loyal and profitable customer is more commercially valuable than chasing a potential new one where the lifetime value to you is uncertain. Customer quantum values operate along the same 80/20 lines as product sales figures.
A small number generate the most sales, usually the most profit and the least debt risk. Therefore it is really vital to know who these customers are, what is important to them, what they’d like to see improved and to be taking the most effective actions to ensure that they are well and truly locked in. The lifetime value of the key customers (say top 10% of spenders) is a highly insightful metric. These customers are exceptionally important and difficult to replace. Erosion in this group will undoubtedly hurt the business.
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A deep understanding of customer transactional behaviors ensures the continued good health of the business and must be an essential monitoring requirement. Defining the baseline is step one: what defines an active, a lapsed or a lost customer? Also: the size and health of the customer file, those active, visit numbers, purchasing frequencies, transaction values and order mix: walk-in, click & collect, delivered, web and app. These are the signposts to identifying patterns and trends in spend frequency and values. I’m a great believer in patterns. Once established they are very hard to influence. For example I could tell by mid-September last year that the first choice striker in my football team (answers on a postcard) was never going to live up to his outrageous transfer fee – the pattern was established early in the season.
Customer churn is a key metric of data. It is the silent killer – the number of customers lost in a given period. Churn determines the day-to-day vitality of the business. Most customers order predictably: daily, weekly, fortnightly etc. By regularly analyzing purchasing patterns it is relatively easy to predict when a customer is heading to towards the exit. Equally by checking over order values in a similar way it becomes clear whether or not a customer is increasing or reducing their purchasing from you. In both cases this simple operation offers management the opportunity to take the appropriate action to reverse what could be become an established debilitating pattern.
In these resource-constrained times where tough choices have to be made, time spent in customer file analysis and data is a better investment than chasing down new customers. This is not digital it is simply good management.
David Gilroy is the founder and managing director of Store Excel
