Why promotions aren’t all that they could be (and how to turn that around)

Posted on Posted in Blog

WHY PROMOTIONS AREN'T ALL THAT THEY COULD BE (AND HOW TO TURN THAT AROUND)

Ever notice the big displays sitting at the ends of the aisles in supermarkets, or how jammed your letter box is with specials catalogues from your local pharmacy or hardware store? Of course you have, as these types of ‘trade promotions’ like price cuts, loss leaders and multi-purchase discount offers are ubiquitous in today’s retail environment. In fact, it’s estimated that a typical retail chain will spend around 15% of its total annual revenue on these promotions.

Despite this big commitment, however, many retailers are unable to optimise the effectiveness of their promotional programmes — instead repeating similar activities every year with little understanding of what influence they’re actually having on customer behaviour — or how they could be improved to lower costs and boost revenues. The reason for this lack of analysis and review is complexity. The success of promotions is dependent on many factors — everything from competitor activity and consumer behaviour, to media cut-through and out-of-stocks, store location and of course, the weather. Answers exist, but for most, the resources required to extract them are not available internally — and true insight remains buried in spreadsheets & data silos across the business.

The solution
It is possible, however, to unlock the value in this data and optimise promotional effectiveness. Datamine, for example, with over 20 years’ experience in this area, has developed a framework of analytics solutions that can be laid over data from any promotional activity — identifying opportunities to cut costs, improve bottom-lines and redirect spend into potential growth areas. Solutions are modular, meaning the areas of greatest need can be addressed first and analysis expanded as required. Some foundation solutions include:

  • Promotion planning and optimisation
  • Campaign planning, assessment & reporting
  • Pricing & scenario modelling
  • Sales forecasting
  • Media effectiveness
  • Customer buying behaviour
  • Customer cross-sell modelling
  • Loyalty program assessment
  • Pricing audits / regulation adherence
  • Store location analysis
  • Out-of-stock measurement
  • Next best offer modelling
  • Post event analysis and effectiveness
  • Catalogue optimisation
  • Customer footprint analysis

The process

While the techniques are proven and the fundamentals similar across different retail sectors, any organisation looking for assistance with promotional optimisation should opt for a service provider that adopts a consultative approach. We recommend the following three step process, for example:

Step 1 : Both parties get together and identify the challenges facing the business — and where the opportunities to optimise your promotional spend

 

Step 2: Working collaboratively, a data-driven solution is developed to deliver on the value equation and address the identified business challenges

 

Step 3: Implement and support the agreed solution— ensuring practical, commercial outcomes with a return on investment typically achieved with subsequent promotions.  

 

 

Use Case

£380k analytics project delivers net benefit of £190k + per week

The challenge
Anecdotal evidence at a large retailer indicated that out-of-stock issues were potentially having an effect on sales, but justifying additional investment into distribution was difficult because the lost revenue from out-of-stocks could not be quantified. The retailer had tried and failed to perform these analytics using only supply-side information.

The solution
Datamine was asked to examine the problem and by adding demand-side analytics was able to provide a good estimation of the cost of out-of-stocks at a product and store level. This not only helped with the investment decision, but also had the added benefit of highlighting what proved to be significant disparities in operational effectiveness between different stores — enabling systemic changes to be made which ensured ongoing effectiveness.

The result
The results of the double benefit were quickly seen as by improving stock availability and out-of-stock processes, the analytics project rapidly delivered a net benefit of nearly two hundred thousand pounds per week.