How AI can help CPG Revenue Growth Management

Praveen GopalakrishnanPraveen GopalakrishnanCEO, Co-Founder Snap2Insight AI image recognition providerMike SweeneyMike SweeneyFormer SVP of BANG Energy 27 years CPG industry veteran

Key Takeaways

  • Retail pricing dynamics in today’s Consumer Packaged Goods Industry has been disrupted by the pandemic in the short term, and is here to stay with increasing impact from ecommerce retailers and services.
  • Dynamic ‘micro market pricing’, Regionalization are exposing large gaps in traditional scan/syndicated pricing data inputs to support effective Revenue Growth Management.
  • AI image recognition technology offers an effective way to provide accurate store level pricing data quickly, and enable Revenue Growth Managers to get ahead.
Revenue Management: Data Gaps

How does Revenue Management help?

I would refer to Revenue Management as the “unsung hero” within the finance department as they are often caught in the middle between corporate finance and field sales. Ultimately, their role is to help Sales build value for a brand’s products while ensuring the company hits profit targets. The pricing strategies built by Revenue Management, taking into account Product price elasticities, competition strategies, COGS, and trade investments to name a few, often determine the difference between winning/losing share and overall company profitability.

Tell me more about the relationship between Revenue Management and Sales.

In most CPG organizations, Finance and Sales usually have healthy tension. Sales tends to maintain a more “optimistic” view of ROI from investments in price or a customer’s marketing program. The goal typically is to convince finance to release funds to support these events. Afterall, the more funding a salesperson can get, the better chance of reaching sales targets. Finance, on the other hand, is typically more conservative, focused on profitability. The tension comes somewhere between driving topline sales at the expense of profit. Revenue Management is perfectly positioned within the organization to act as a “bridge” serving the role as a Business Partner to Sales.

What are the current tools being used by Revenue Management?

There are many tools to help Finance develop profit models. One blind spot in my mind is store level visibility. Although there are traditional syndicated data tools such as IRI or nielsen, this data simply can’t support reactive, micro-market pricing decisions needed to maximize profit. Whether you are a company that is large or small, there are always challenges getting the data needed to accurately assess what is happening with the brand at retail. Although Revenue Management is a key Business Partner with Sales getting their attention is a common frustration.

Can you talk about an example where having store level pricing data is important but is hard to get today?

There are many barriers to overcome across different retail channels that make getting store level pricing data. In the convenience channel, for example, roughly 40% of the retail stores are considered “Independents”. For certain categories such as tobacco and energy drinks, this channel is incredibly important in driving sales while very hard to execute consistently as every store operates on their own, without the direction from a corporate buying team. Unfortunately, it’s also the least tracked by syndicated data resulting in inaccurate data.

Are there other channels that stand out in your mind?

I believe all channels and retailers where syndicated data and retailer store level data is hard to obtain (either they won’t provide or too cost prohibitive) create gaps for Revenue Managers. Hardware Channel (Lowes, Home Depot, Ace/True Value), Natural Channel (Sprouts, Whole Foods), Sporting Goods (Dicks, Academy) come to mind. Retailers have the legal right to determine retail prices, however, their decisions can impact your brand which can create problems for the P&L.

Can AI help revenue management?

I’m wondering, can AI-Image Recognition technology help?

Absolutely! I’m sure many Revenue Management teams are aware that this technology exists, however, it’s a tool that should be deployed. Although there are many tools to model price elasticity and pricing strategies, the INPUTS for these models are critical. There is nothing worse than building strategies on WRONG inputs. I think this technology can arm a Revenue Management team with the most absolute data from what’s actually happening at any given store, micro-market, region etc. I love that this tech can report category pricing data as it is executed at the shelf- including competition.

Have you thought of any other ways AI-image recognition shelf data can be used?

As I mentioned earlier, getting and maintaining the attention of the Sales organization is hard for the Finance Department. Trying to get sales to commission a price audit is especially hard as initiatives are often manual which creates unplanned, incremental work for a strained resource often resulting in poor data. I see AI-Image Recognition as a tool that can work within the current constraints by simply taking a picture, a picture that is probably already being taken by field force, saving time and money without creating more work. Once the picture is “learned up” sales will start to see that promotional execution and OOS are real issues negatively impacting ROI.

Seems like pricing audits are usually a “one and done” project?

It shouldn’t be. Strategically, brands are obsessed with what their competition is doing with regard to pricing both everyday and promotionally. For leading brands, the Retailer is now implementing pricing strategies for their brands. Because it’s such a burden for sales to consistently execute pricing survey’s, it does often become a once or twice a year project. I think AI-Image Recognition should be the unlock for brands and Rev Management to track and trend pricing actions throughout the year. And if all it takes is for field-reps to click photos of the set, and rest everything including extracting pricing, rolling up data is done by AI, field sales should have no difficulty in getting the photos every store every visit.

Any final thoughts?

There is no doubt that the CPG world is changing rapidly and traditional tools to gather data are either too costly or underwhelming. Yet, the decisions that need to be made to drive the P&L require more detail and better data. AI-Image Recognition is a tool that will become critical in how brands make pricing decisions for their Brands.

Let us show you...

From concept to results for your Brand in 30 days