The following is a guest post from Susan Dunn, chief revenue officer at NielsenIQ.
It’s no secret that small, up-and-coming brands face an uphill battle in today’s CPG environment. Emerging brands often lack the budgets and data that can help get their products into stores and keep them on the shelves. Competition is fierce in an industry predicated on sales and distribution.
But it doesn’t have to be this way. CPG data isn’t equal and certain metrics can show promise, even if sales and distribution are modest. This is why smaller brands need to empower themselves. With the right retail data and analytics, emerging brands can play velocity, panel data and incrementality to their advantage.
Velocity. The first metric an emerging brand should play to its advantage is velocity, more commonly known in the industry as “$ per TDP.” Velocity measures how well a product is selling ($) where it’s available (total distribution points, or TDP).
Velocity helps to gauge the success of up-and-coming brands. Retailers know that startups can’t compete with big brands directly on metrics like volume. Since sales isn’t a fair comparison, smaller brands have to prove that consumers who love their products will keep coming back for them. By leveraging velocity, small CPG brands can illustrate the likelihood of sales growth to earn more shelf space or win distribution with new retailers altogether.
Panel data. This form of retail measurement highlights the consumer preferences that are driving or shifting sales. Panel data is also known as “household data” because it comes from NielsenIQ’s panel of households. Participating households scan the barcodes on products they purchase and indicate where they bought the products.
Panel data yields valuable insights for small brands – customer loyalty, consumer demographics, purchase cycles and more – that help inform decision-making. To play this metric to their advantage, CPG manufacturers should work through the four steps of the panel data decision tree:
- How did sales change – did they increase or decrease?
- What drove the change: the number of households purchasing a product or the amount of product each household purchased?
- If the amount of product each household purchased drove the change in sales, was it because of purchase size or purchase frequency?
- What other factors could have influenced the sales – outlet importance, loyalty, percentage of repeat buyers or percentage sold on deal?
Brands can take the resulting decision tree insights and use them to formulate or adjust business plans. For instance, a manufacturer might employ programmatic ads or influencer marketing to boost customer acquisition. A brand could implement “must-buy” deals, such as 3 for $9, if the consumer purchase amount per trip had dropped. For expandable consumption categories, “buy one, get one” discounts are another popular tactic employed when consumer purchase frequency is down.
Incrementality. The last metric emerging brands should play to their advantage is incrementality. Retailers want to add items that will expand the category rather than ones that can easily substitute for another product.
Chocolate milk is a good example of this. White milk will outsell chocolate any day. But when shoppers buy their standard white milk, CPG data indicates they sometimes add in a carton of chocolate too. The result: Chocolate milk leads to more milk purchases overall, thus growing the entire category size. The lesson here is while sales may be small, a product can still be additive to the overall category. Incrementality can be a huge differentiator for brands that can prove data-driven strategy leads to category expansion.
For up-and-coming brands to survive and flourish in today’s competitive CPG landscape, they need to illustrate why they’re diamonds in the rough. Their size shouldn’t preclude them from having the hard numbers and credible data sources to make their case. Knowing the metrics to play to their advantage and having the technology to access them, emerging brands can go a long way.