Proving The Power Of Awareness Campaigns Across Facebook & Youtube

After dedicating almost a year to collaborating closely with our esteemed client, OVO Energy – the leading independent energy supplier in the UK, committed to guiding its members towards a carbon-neutral lifestyle – our boosted Facebook sales for OVO by an impressive 360%. However, fueled by our relentless pursuit of even greater efficiency, OVO and our team became intrigued by the intricate dynamics of their brand’s marketing funnel, specifically the correlation between entry and exit points.

Challenge

While we understood the key elements that contributed to a high-performing conversion ad, we were yet to grasp the precise impact of awareness activities on the ad’s effectiveness.

• Would potential customers be more inclined to convert if they were initially exposed to information about the product?
• Which platforms proved most effective in educating consumers before they made the decision to sign up?

Driven by determination to unravel these mysteries and accelerate OVO’s business growth, we embarked on a transformative shift in focus. We directed our attention towards investing in a comprehensive full-funnel test, aiming to ascertain the extent to which consideration activities had a statistically significant impact on sales.

Strategy

To determine the impact of our mid-funnel activities on the lower-funnel direct response (DR) activities with statistical significance, our team employed various methodologies in our analysis. With these different approaches in mind, Realtime embarked on developing a well-structured testing strategy. We implemented a randomized division of potential targets for each campaign based on the UK regions.

One of the methods utilized was ANOVA, also known as Analysis of Variance. ANOVA enables us to ascertain whether the average outcome of our test group is statistically distinct from the average outcome of the control group. It also allows us to investigate whether this difference is attributed to the variable under study or merely due to chance.

Another method employed was ANCOVA, which stands for Analysis of Covariance. Through this approach, we were able to account for independent variables that varied across groups and might have influenced the test results. By controlling for these variables, we minimized the likelihood of their impact skewing our test findings.

We also utilized Pearson’s R, also known as Pearson’s Correlation, to examine the strength and direction of the linear correlation between two variables. This method helped us understand how closely and in what manner these variables were correlated or proportionally increased/decreased in relation to each other.

During the testing period, Region 1, the control group, exclusively received conversion ads. In contrast, Region 2, the test group, was exposed to both Youtube and Facebook awareness ads before being served the conversion ad.

Results

After a duration of 6 weeks, the experimentation reached its completion.

Sales within the designated test region witnessed a remarkable surge of 45% compared to the sales recorded in the control region. Consequently, OVO Energy enjoyed a substantial increase of 1.4K in additional sales.