Post by YY Tsang.
Sales reports do not always tell the full story
Your customers are costly to acquire and often slip away too easily. Wading through lengthy, standard sales reports is not all that enlightening when you are trying to understand why your sales are falling below the expected levels.
Without some underlying number crunching and behind the scenes analysis to help you with your task, before you know it some of your customers have gone elsewhere and it’s too late to rescue your sales targets.
Such was the case with one of our customers, a nationwide food distributor. Their Sales were up year on year but not as much as they expected. It was difficult for them to pinpoint why this was happening, because the overall picture obscured the details of what was causing their problem.
They asked us for help in creating some BI routines that could automatically alert them to the reasons for the shortfall, and at the same time help them to retain their most precious asset, their customer base. We came up with a solution that incorporated our 3 step approach to BI insights – integrating their data, understanding their issues and applying some business rules to address them, and finally visualising their sales exceptions so that they could take immediate action.
By understanding their customer behaviours before it was too late to do something about it, they managed to reduce the churn of regular customer by 16%, and increase overall sales by 3%.
As you can imagine, this had a welcome and significant impact on their bottom line.
Our 3 Step Route to Success
Step 1 Integration of Data Sources
We started by integrating their relevant data sources. We extracted sales data from their back end ERP system and some Excel lookup files which they were using to categorise certain data sets differently from the ERP system.
Step 2 Understanding the Business
We applied some analytics and business rules – in this case we split customers into 3 groups – high value (Premium), regular and others. This helped them focus automatically on the important sections of their customer base.
The background calculations we devised established a typical buying pattern for first 2 groups of customers as a combined account for the majority of overall sales.
The routines also identified customers not following the expected buying pattern.
Step 3 Visualising the data appropriately
We created a portal to visualise the data in such a way that it was easy for them to identify those customers not following the expected buying pattern. We created users for the portal from their Telesales department and their Sales team and allowed them logins to the portal to monitor the behaviour of the groups, and the exceptions.
How it helped them
The key differentiator from the standard sales reports they had been using up to then was the automated analysis and filtering at Product Family level to identify possible customer defection before the customer was lost.
We suggested a weekly review of the exception reports with follow up from Sales / Telesales staff.
As reported above, this resulted in reduced churn of regular customer by 16%, increasing overall sales by 3%.
Here are some examples of the screens they use
History of Regular and High Value (Premium) Customer Groups. Note the Rep is looking at his/her own customer data and is looking at all period for 2015 so far.
The Regular Lost Customers’ Order Pattern (9 in all). He has selected ProdDept = Overall to identify if the customers have stopped trading altogether. These customers last traded 2 months ago.
The next step is to investigate Customer Product Pattern. He can identify which Product Families have customers who are not following the buying pattern and are slipping away. Then he can target these for particular products. Here he has selected ProdDept = Champagne. There are 7 customers to follow up with a visit or a call.
About YY Tsang
YY Tsang is Managing Director of Data Management Business Insight. YY began his IT profession in 1986 managing IBM mainframes before moving to Asia to work in business automation, client management and solution consulting to multi-national and government clients. Industry sectors managed include mobile operators, banking and finance, manufacturing, utilities and library. YY brings together a strong business operations background with technical skills in Diver to offer customers meaningful business insight to boost business performance.
Since joining the Diver BI Group YY has developed specialist skills in designing and delivering BI applications for mobile technologies including iPad and other tablet computers.
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