by Thalya Hamilton
Vice President, Client Analytics at Ibotta
How to drive 49%+ median incrementality while going beyond typical metrics to understand shopper behavior
Every marketer and marketing research professional has heard some variant of the following: ‘Half my advertising spend is wasted; trouble is, I don’t know which half.’ While having become cliched, the statement rings truer by the day with new tech and tactics bringing new performance indicators to sort through, new data sources to vet, and a slew of Qs:
Are you tracking the appropriate KPIs? Is the measurement methodology or approach sound? How reliable is the data source?
Of course, there’s no ‘one size fits all.’ A proper approach to measuring a broad scale TV ad campaign would be unrecognizable to someone who’s exclusively kept to measuring social influencer campaigns. Success criteria will differ between intent to expand the base and drive trial versus intent to encourage existing buyers to purchase more.
To become the #1 consumer rewards platform for brands and retailers, the Ibotta team knew that delivering an amazing experience with extensive content, or unprecedented scale — it wouldn’t be enough. Since proven performance to brand and retailer partners was also essential, the Company adopted four fundamental principles to drive that success.
4 FUNDAMENTAL PRINCIPLES
Let the strategy determine the KPI
Ibotta’s Client Partnerships team focuses on understanding clients’ objectives, advising on targeting strategies, and aligning on how to measure success during and post campaign. The Company’s analytics capabilities are robust yet agile, providing in-flight monitoring of key leading performance indicators as well as end of campaign buyer decompositions, sales lift and incrementality — all specific to what means most to the brand.
Measure at the level you execute
Ibotta communicates with consumers, i.e., people. Not markets, not stores, not cohorts. Measurement is at the user level, enabling brands and retailers to go beyond typical ROAS or iROAS metrics to provide insights into impacts to shopper behavior.
Avoid bias in methodology
Ibotta has adopted an experimental design approach, such that if incrementality is an aligned-upon KPI for a given campaign, a randomized 5% holdout is created during campaign setup and withheld from the treatment. This holdout is used to establish the baseline for sales during the campaign period.
Once the campaign is complete, campaign-period sales of the treatment group is compared to that holdout, projecting to total population. The difference is then tested for statistical significance.
Utilize the most complete and quality data
Having the largest panel of verified buyers with omnichannel purchase information, Ibotta limits the measurement sample to the linked loyalty card population, where both incentivized and organic purchases are captured. Since shoppers are incentivized to upload receipts, it’s possible that the inclusion of individuals without linked accounts would overstate incrementality — a bias to avoid.
In addition, Ibotta does not see the full history of transactions for this subset of receipt upload only and cannot provide additional insight into whether buying behavior truly changed as a result of the campaign. Diagnostics such as buyer segment results and share shift would not be reliable.
PROVEN, REAL-WORLD PERFORMANCE
With this tried and true, four-principle method, Ibotta has conducted over 3,600 tests, allowing for campaign benchmarking and category comparisons. Across all statistically significant results, Ibotta drives a median incrementality of 49.9%.
With proven performance, proprietary 1:1 omnichannel purchase data, Ibotta delivers.
- Targeted promotions
- Incremental sales
- Unrivaled data analytics
- Unprecedented scale
Know your source. Get in touch with your Ibotta rep or inquire here to learn more about identifying new opportunities for effective promotional strategies.
Written by Thalya Hamilton
Thalya Hamilton is the Vice President of Client Analytics at Ibotta. She's been a market research, product, and data analytics specialist for nearly two decades. Prior to Ibotta, Thalya led teams at Nielsen and Quotient.
