Maximise Your Data

Improve profit using micro-segmentation of your data

• The main objective of MYD is to identify and fix those portions of your sales that are not achieving their profit potential. Even if your overall business or segment of business is profitable, it will be made up from high achieving sales, low achieving sales and everything in between. By definition there will always be below average sales.
• Segmenting the customer and product data into small distinct groupings enables us to break up the sales data into millions of micro-segments. By analysing these sales, we are able to identify the low profit achievers.
• Each micro-segment may have only a relatively small contribution, but when you add say 300,000 of these together, the results can be stunning. Having fixed one level of issues, the criteria can be tightened and made more specific to find even more opportunities.

An analysis with one wholesaler highlighted a 7 figure opportunity on this initiative alone.

Grouping customers for price and discount consistency

• Another initiative identifies groups of customers who could receive common base pricing. Any customer specific terms will override these background levels. By setting comprehensive – and most importantly – realistic sets of prices and discounts, we were able to increase profit margins by between 2% and 4% on the segments of sales targeted.

 3 separate projects all returned approximately 4% gross margin improvement which resulted in a total of £410k pa profit improvement.

• This was all driven from the system held data, therefore the margin increase was instant. Also, because the generic pricing and discount levels had been carefully calculated based on sales history and customer segmentation, the level of adherence to system held pricing stepped up by 10% (a 25% increase). This meant that 150 thousand additional order line transactions per annum were now made using system held data instead of using guess work.
• In these examples, no customer consultation was necessary as the background discounts only kicked in if there were no customer agreed terms. All action was carried out from behind a desk!
• We can then start removing the inappropriate customer specific pricing to get further consistency and control. With greater control comes the ability to start pro-actively managing customer pricing.

 Discount setting tool

• As well as correcting erroneous or inappropriate data, we should be preventing it being input in the first place. Unfortunately, the goal posts are continually moving. Discount levels can go out of date as trade or list prices change out of line with cost price changes, so impacting on the available discount and affecting profit margins.
• Changes of product mix within the groupings can also affect the dynamics and influence the discount levels. Previously good data can become outdated, so needs to be caught in the audit processes for review.

 The MYD discount guidance tool is dynamic and therefore able to accommodate these changes.

• MYD have developed a flexible discount guidance tool that is tuned to specific customer segments. Using the MYD developed algorithm, proposed discount levels are calculated by product discount group tuned within customer segment.
• This technique can also be reversed to aid the setting of list prices for either own brand ranges or other product ranges with no published trade prices. This way we can ensure that the prices that result from a group discount are consistent and make the appropriate margin.

 These are just a selection of the techniques we can use to unlock the hidden profit in your Data. 

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