SVP of Sales Stacy Bohrer shares why CPG marketers have long struggled to align ad budgets with product sales, and how brands can finally bring the digital age to retail marketing.
The modern marketing profession is built around using precise customer and sales data to reach customers in just the right places. But in the world of retail CPG, marketers have had to operate without the precision of their peers.
Despite the widespread use of beautiful, sophisticated tools for digital marketing analytics, CPG marketers continue to rely on ancient, hard-to-read retailer reports for what’s arguably the most important data for their business—the information on where and how products are selling.
Why are CPGs sitting on data that can’t be used by marketing teams?
Before coming to Crisp, I worked at The Trade Desk, the most advanced Demand Side Platform in the world, for nearly eight years. I worked with the biggest CPG brands on the planet and saw the inner workings of the most savvy marketing teams for every channel. When it came to how brands and retailers were using data to improve marketing and advertising, I thought I had seen it all— their struggles for precision, their eagerness to use data from retailers more effectively, and the rise of Retail Media Networks. In an industry that places its highest value on first-party data, CPG companies knew they faced a challenge based on their lack of it (how many people visit Kelloggs.com to buy their cereal?).
When I came to Crisp, I realized that there were valuable data sets hanging out in Excel files across the organization, but they were siloed —leaving marketing teams in the dark. In this post, I’ll explain why this is a major roadblock to growth, including:
- Why the sales-to-marketing information gap is a big leaky bucket for maximizing ad spend
- What kind of data marketers need to optimize campaigns and increase Return On Ad Spend
- How to turn on real-time data sharing to make CPG marketing more effective
By the end of this article, you’ll know how to spend based on store-level insights instead of guessing, and your sales team will thank you for no longer having to bury themselves in mounds of excel sheets. Let’s go!
The Problem: An information gap between sales and marketing
When a customer buys something online, there is no shortage of data – including age, order history, location, and similar interests – that marketers can use to better understand trends and target consumers. For instance, marketers can see with e-commerce data that a product is selling well with a specific demographic (say, 40-60 year olds), but isn’t getting traction in another (say, 18-25 year olds). This knowledge helps them optimize ad spend by targeting the age group that loves the product more.
However, when it comes to storefront locations with physical retail, that data is lost. That’s because there hasn’t been a system to organize the information consistently, understandably, and quickly enough to make it back to the marketers.
Up until now, retailer data has only been available in spreadsheets or vendor portals – but it might as well be in a different language for each retailer, as each uses their own system to track and format the data. This leaves CPG marketers unable to gain proper insights, because there’s no normalized, clear picture across all retailers.
While IT teams and analysts can normalize the data, it can take weeks, rendering it out of date by the time it gets into the marketing team’s hands. This means that marketers and their vendors aren’t able to use the data effectively, because it’s in the wrong format, it’s out-of-date, or both.
Here’s why that needs to change:
- Advertising spend is being wasted on products that are currently out-of-stock. Marketers know this, but without timely retailer data, there’s nothing they can do about it.
- Supply chain challenges have made this problem worse, causing brands to shut off advertising altogether because they don’t know where inventory is available. There needs to be a way to re-allocate that spend, rather than turn it off.
- Leveraging retail data will become the new norm soon enough – but marketers have the chance to be on the leading edge now
I’ve asked over 100 marketers if this retail data is valuable to them, and they all say yes; they’re just not leveraging it because they don’t know how to access it.
The Solution: Real-time data mined, sorted, and made usable
Crisp brings the digital age to in-store retail, all with the use of existing POS and inventory data. Crisp connects to retailers and distributors to ingest and normalize their data, giving sales and marketing teams immediate access. The data is then presented in usable visualizations or piped into core business tools, helping marketers leverage a 360-degree view of timely, location-based data down to the individual store.
Access to normalized, real-time data is a game changer because it:
- Keeps your sales team from having to pull reports manually, saving hours per week
- Gives marketers and other business teams access to actionable data in real time
- Finally gives advertisers the precision to do their jobs effectively and confidently
Sacred Serve, a gelato company using Crisp, saw sales increase 20-50% because the marketing team was able to go from quarterly sales reports to weekly sales reports—enabling a faster feedback loop that drove smarter decision-making in advertising.
Why CPG brands need to take advantage of this yesterday
Thankfully, marketers are no longer left to guesswork – because Crisp has made the information they crave available and usable. And now that this data exists, there are no more excuses for wasted time and ad dollars.
Here are some things marketers can do with usable, timely retailer data:
- Geographically target ads where product is actually in-stock, driving ROAS
- Time campaign activation exactly when a new product hits the shelves at every store, making launches more effective
- Promote products nearing expiration at a given store, driving sales and reducing waste
- Tailor ad spend to store-level sales performance, driving measurable sales lift
The results are in: using data effectively for smarter, more precise advertising improves ROI and drives measurable business impact for brands.
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