I saw this interesting McKinsey piece recently – Rediscovering the art of selling – McKinsey Quarterly – Retail & Consumer Goods – Strategy & Analysis – and I was struck by the value of analytics in this context. What retailers really need to do, according to McKinsey, is focus on hiring sales people with personality, extroverts motivated by helping customers.
I saw this interesting McKinsey piece recently – Rediscovering the art of selling – McKinsey Quarterly – Retail & Consumer Goods – Strategy & Analysis – and I was struck by the value of analytics in this context. What retailers really need to do, according to McKinsey, is focus on hiring sales people with personality, extroverts motivated by helping customers. And they need to spend time training this folks on sales techniques, approachability, reading body language (to tell who wants to be left alone) and much more. Do this, the article says, and your closing, cross- and up-selling will be far more successful. So far so good.
But the reality of a modern retailer is that there are a tremendous number of products with lots of potential cross- and up-sells to choose from. Even someone with the skills you need might not be good at, say, color matching making it hard for them to make the right clothing choice for an outfit. Add in multiple discounts, loyalty programs and other forms of dynamic pricing and you have a complex environment. Retailers feel that have to invest resources and time in training staff about these things, reducing the time available for sales skills training, and even that they must hire for an ability to understand this complexity even at the expense of the personality and sales skills they need. A case of being between a rock and a hard place?
No, enter analytics. With decent analysis of their historical data and a focus on the decisions that have to happen during the sales process, retailers can spend their time and energy training staff on the sft skills they need and let their systems and analytics do the rest of the work. They can use business rules/analytics and decisioning to answer questions like what discount does this customer get, what’s the best up-sell for this customer given their purchases, what’s the best cross-sell that will complete the outfit they are buying. They can analyze sales data, loyalty card data and external data and use rules derived from this data or from their best sales people. If they adopt the “swipe first” loyalty card approach they can empower their staff to do even more by leveraging everything they know right at the start of a conversation.
Your staff don’t need to be able to make all these “technical” decisions – you can build systems that act as effective advisers to them freeing them to work on their people skills, customer interactions and actually selling.
Copyright © 2010 http://jtonedm.com James Taylor