A retailer asks a manufacturer's sales rep, "Why isn't your new product flying off our shelves?" The salesperson hems and haws, then finally admits, "Our national advertising and promotions haven't started yet. Let's wait and see how our new product performs once we start really supporting it!" This wait -- often 8-12 weeks or longer -- is a drag for all parties, from the manufacturer to the retailer to the consumer. But what's the alternative? No one wants to start promoting a new product until every single store is stocked -- after all, who wants to advertise to empty shelves, right?
It's been reported that CPGs will invest more than $70 million when bringing a new product to market. Roughly 75 percent fail to reach $7.5 million in sales after a full year on store shelves. With more than 20,000 new food and beverage SKUs introduced to market each year, manufacturers and retailers face a host of logistical, sales, and promotional challenges: Consumers are fickle, trends come and go, and what sells in one store and/or area of the country may flop in another.
For years, manufactures and retailers have used point-of-sale (POS) data and supply chain management systems to maximize their in-store availability in every store, every day. Now, these same parties are using the same data and systems to understand and impact consumer demand -- what's selling, where, and why -- in every store, every day. Forward-looking marketers and agencies on both sides of the table are integrating daily, store-level intelligence (about product sales and inventory) with digital marketing platforms to automatically deliver their campaigns when and where they are needed to maximize incremental in-store sales. For the first time ever, marketers can automatically deliver advertising based on daily, store-level demand and can measure the incremental sales impact of their advertising in near real-time -- successfully answering the oldest question in marketing: "Did my ad spending increase my sales?"
Take for example a shopper marketing director who is looking to accelerate the sales of her new product at one of the nation's largest grocery chains. Now, that marketer can partner with multiple ad networks, who integrate daily POS analytics into their platforms, to accelerate sales in each store as quickly as possible based on the first day each store starts selling her new product. That marketer doesn't have to wait 8-12 weeks to start supporting her new product, her sales team is saved from another awkward conversation with the retailer, and the consumer is delivered a highly actionable message telling her exactly when and where the new product is available in stores near her. The result? Happy customers all around and an incremental 6.7 percent in-store sales for the average new item launch.
Similar improvements can also be seen for agencies and marketers when they are advertising their existing items. For instance, take a leading CPG manufacturer selling items across a variety of categories. It's been shown that that CPG can drive 80 percent of their sales by targeting consumers surrounding 57 percent of their top-selling stores, with the number and location of stores varying wildly by brand. In fact, there are many multi-million dollar SKUs that deliver 80 percent of their sales in less than 40 percent of stores. When this store-level intelligence is integrated with digital marketing platforms, the results can be impressive. Integrated campaigns for existing items can deliver just under 5 percent incremental in-store sales for the items featured in the campaign and almost 3 percent incremental in-store sales for all other items in the brand (also known as "halo" items).
This unique integration of daily, store-level intelligence and digital advertising strategy is now allowing brands and retailers to maximize the impact of their new product launches, in-store promotions, and seasonal offerings. Just as importantly, agencies and marketers are also using this intelligence to continuously measure their digital-to-store ROI, helping them become "business builders" vs. "investors" and giving them a seat at the head of the table. Other key takeaways and tips to consider follow:
- Timing matters: Delivering ads to the right consumers, near the right stores, at the right time is the goal. Deliver too soon and you drive unforgiving consumers to empty stores, too late and you fail to drive demand in tune with supply.
- Location matters: Spending dollars where you make dollars is a no-brainer. If the first 50 percent of your budget drives 80 percent of your sales, then the last 50 percent of your budget will drive 20 percent of your sales. You don't need a Ph.D. to understand this, you just need a scalable solution to automatically integrate your store-level intelligence with your digital delivery across as many platforms as possible.
- Optimization matters: Once you handle the basics (timing and location), the next step is to optimize delivery during your campaign. The average brand campaign is roughly 30 days long. This is far too long to "set it and forget it." The most intelligent solutions in this space are optimizing hyper-local delivery multiple times throughout each campaign based on daily, store-level data.
- Proof matters: The oldest question in marketing is, "Did my advertising increase my sales?" The second oldest question is, "What can I do to continuously improve on this metric?" For marketers working in a closed-loop ecosystem (such as technology or financial services) answering these questions is relatively straightforward -- but for CPG and retailer marketers, who sell 94 percent of their products in physical stores, these answers have been elusive for far too long. Is it any wonder then, that the average tenure for a CMO in CPG or retail is 18 months shorter than the average tenure for a CMO in technology or financial services? The industry needs to broadly adopt scalable solutions for closing the loop on digital-to-store ROI and achieving the power of proof that their digital campaigns are driving in-store sales.
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