Use Behavioral Insights to Develop Better In-Store Promotions

by   |   March 23, 2015 5:30 am   |   0 Comments

Jamie Rapperport, co-founder and CEO of Eversight

Jamie Rapperport, co-founder and CEO of Eversight

Each year, the consumer packaged goods (CPG) industry spends $300 billion on trade promotions. That’s over 17 percent of revenue at an average CPG and nearly twice what they spend on marketing, and the number is only growing. Despite this high level of investment, any consumer goods leader will tell you that more than half of all promotions fail to deliver a positive ROI, and many lose 50 cents on the dollar.

Most in-store promotions are ineffective because there is no effective method of finding new, winning promotions without taking big risks. In a world in which missing a promotion week can mean missing your volume target for the year, who can afford to take a risk on something without knowing it’s a winner? So CPG companies recycle the same old promotions week after week, year after year. Inevitably, shoppers get used to them, and the promotions become stale and ineffective.

 

Looking Backward Instead of Moving Forward

Today, most CPG companies use “post event analysis” software, commonly known as Trade Promotion Optimization (TPO), to track their trade promotions. TPO software helps companies measure the results of their promotions after the event is complete, relying on econometric regression analysis to sort through large volumes of aggregated point-of-sale data.

These systems are helpful for tracking how well you did after the fact, but they aren’t designed to help you identify new promotions to run next. This existing approach is, at the very best, 20-20 hindsight. It’s good for seeing where you’ve been, but it can’t tell you where you ought to go. It’s about reporting, not innovating.

Related Stories

Podcast: How analytics can help retailers put goods where buyers want, and when.
Read the story »

Redbox finds new kiosk sites by tracking DVD rental behavior data.
Read the story »

McDonald’s moves to franchise-level analytics to elevate performance.
Read the story »

Focus On: Retail Analytics.
Read the story »

In the last 15 years, a new field, called Behavioral Economics, has come to prominence. It seeks to understand people’s economic decision making by looking to psychology rather than traditional economics. And it brings an exciting message: Consumers are much more complicated than previously thought, and they’re moved by many things other than money. This is welcome news for brands – it means a straight discount isn’t the only way to drive response and lift. But this new view also highlights what a complex world we live in: There are an infinite number of ways to frame an offer. How can we possibly know which one is best?

It’s useful here look to e-commerce retailers, who have used online testing – aka A/B testing – for years to collect data to help drive higher online sales. This approach enables digital marketers to run balanced experiments to test the effectiveness of ads or website design and, based on the resulting data, to swap out less effective parts (text fonts, colors, etc.) for more effective ones. Recently, armed with knowledge of how behavioral economics works, several leading CPG companies have started moving toward a similar testing approach for in-store promotions.

Called “offer innovation,” this new method of digital testing enables companies to test offers by experimenting with different offer structures, depth of discounts, images, products, quantity, calls-to-action, etc., and collect data on all of it. The test promotions are served to small, balanced groups of real shoppers through digital platforms such as social, print-at-home coupon sites, and email, and can be redeemed in store. To shoppers, these “micro-tests” are simply promotions, but to companies they are a valuable source of customer behavior data. By testing a large number of offer variants with shoppers online, companies can get insights into which promotions drive the most consumer engagement.

Most micro-test “campaigns” are executed in about a week, delivering results with high levels of statistical significance. For example, a leading consumer goods manufacturer found that for one of its most popular products, 4 for $5 was, surprisingly, more appealing than the $3 for 3 promotion, which it had been running for years. Similarly, a national retailer found the demand for a grocery item found in every supermarket dropped 43 percent when price was raised by just one cent above a seemingly arbitrary threshold. These insights are then used to inform broad in-store promotions, including end-cap displays and promotional newspaper inserts, across brick-and-mortar retailers.

Digital testing works best in concert with existing systems and processes, injecting much-needed forward-looking insights – insights that are critical to knowing which in-store promotions will maximize volumes, trips, basket size, and ROI. Once proven through digital testing, “optimal” promotions can be added to the promotional calendar and managed through existing promotion systems. And once a promotional event is complete, post-event analysis can reveal how a promotion performed on a number of key in-store measures, potentially providing additional guidance for future testing.

However, today what we see is a process that starts where it should end. Rather than putting consumers at the center when developing new promotions, promotion discussions at CPGs have been too focused on what was run last year. Using aggregated, noisy point-of-sale data fails to take into account the nuances of consumer behavior. Two economically identical offers – such as $1 off a $4 item and Buy 3, Get 1 – are combined into a single 25 percent off data point. We now know that consumer response to different offer structures such as this can vary by 200 percent or more. So which offer would you run?

Jamie Rapperport, co-founder and CEO of Eversight, has 25 years of experience as a software entrepreneur. Prior to founding Eversight, Jamie was co-founder and EVP at Vendavo, the leading B2B pricing technology company. Prior to Vendavo, he served as a founder and vice president of marketing and sales at VXtreme, which was acquired by Microsoft and became the core of “Windows Media Player.” Jamie has a B.A. from Harvard University and an MBA from Stanford.


Subscribe to Data Informed
for the latest information and news on big data and analytics for the enterprise.






Tags: , , , ,

Post a Comment

Your email is never published nor shared. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>