Article courtesy of TELUS Consumer Goods
Trade spend doesn’t have to be the definition of insanity if promotion performance data is analysed consistently and effectively.
In FMCG many companies repeat their trade promotions calendars annually. “Same as last year, with adjustments for Easter,” goes the refrain. But whilst trade promotion spend is one of the largest line items on a manufacturer’s P&L at around 20-30% of revenue, as many as two thirds of trade promotions don’t break even. Nearly a third of companies are thus dissatisfied with their ability to manage promotions. Much of this comes down to a lack of analytics.
Because many companies manage their trade promotion spend using Excel spreadsheets, it’s difficult to see where the spend is going. The chief challenges lie in understanding what’s working and what’s not; how to weed out the poorly performing promotions by understanding the drivers of performance and replacing them with something else. This is where analytics come in.
A centralised, analysable platform helps you gain visibility and control of spend. Optimising ROI – lift, contribution – for future promotion plans and looking at the results of post event analysis (PEA) on a consistent and frequent basis. This includes five fundamental questions all FMCGs should be able to answer about promotional performance after analysis:
1. Did the promotion expected to run, actually run?
2. Did it achieve the expected promotional ACV?
3. Were the projected promotional volumes close to the actual volumes?
4. Are there competitive products that perform well with ours, or vice versa?
5. Was the promotion profitable?
Beyond looking at individual promotions, analytics also means being able to see what works and doesn’t over time, by promotion and by retailer, in order to create ‘norms’. Something that enables visibility of competitor promotional calendar conflicts and performance. Being able to compare promotional ROI for a single event to other promotional events. Being able to see the impact of the mechanic; timing; seasonality; duration; frequency; and discount depth.
Ideally your analytics would also capture true promotional uplifts as increments including pantry loading, forward buying, price elasticity, pre and post promotion volume dips, and cannibalization of your own and competitor products. As well as include ‘store back’ POP attributes including product availability, in-store compliance, regional and geographic considerations, and retailer feedback.
Underpinning trade promotions effectiveness analysis is a good TPO software system. Ideally this centralises and harmonises data such as shipment, spending and pricing. It allows for baseline modelling to reflect true consumer category and brand consumption – past, present, and future - in the absence of promotions. It enables post event analysis, including external data source integrations, predictive lift coefficients, event-based lift, manufacturer and retailer ROI and margin analysis, and competitive and consumer event overlay.
TPO systems provide analytics that can help you very quickly identify where your trade spend is going, working and why, and what to change.
For more information visit www.exceedra.com or contact Luke Pocock at firstname.lastname@example.org