Recommendations based on ROIVENUE's data-driven attribution models saved Econea over 15% of its total monthly marketing budget during the first wave of optimization.
Econea is an e-commerce brand from the Czech Republic focused on selling ecological goods - sustainable, environment-friendly products for daily use. Econea is not only catering to the growing number of environmentally conscious consumers bringing the eco-transformation to the mass market, but is also showing leading the way in digital transformation.
With these efforts the visionary e-shop of young founders has already become love brand and a leader in its category.
The company has grown rapidly in the last few years - from a start-up to established and fast growing e-tailer. Climbing it's way up through marketing maturity, now the time comes to start systematically driving its growth and making decisions based on advanced data. Econea chose ROIVENUETM as their partner to help them with data integration and attribution, including integration of internal systems data which allowed their marketing department to optimize marketing based on pure profit.
After initial attribution analysis within ROIVENUETM, we found that Facebook Business - the strongest channel in terms of investment had a negative Return on Marketing Investment (ROMI) in Markov First order attribution model.
Previously, with only last click attributed knowledge, Econea marketers could not be sure of the precise contribution of the channel and were hoping that along with last click conversions, Facebook ads were helping enough other conversion paths to make its high spend worth-while.
Now, they were sure that this channel was overinvested.
The comparison of ROMI in Markov and last-touch attribution model.
Budget cuts in Facebook Business channel were thus recommended and executed. The result was growth of ROMI in weeks 26-29. Revenue stayed on the same level while ROMI got, finally, to the positive numbers (around 1). The overall effectiveness of the Facebook channel was improved and savings were calculated for 15% of the overall digital marketing budget.
While marketing investment went significantly down (1), revenue generated from Facebook stayed almost the same (2), ultimately increasing the ROMI (3).
Connection of Econea's internal order system to ROIVENUETM also enables for optimization based on Profit and channel position in Path.
Following analysis was done for Criteo, where we identified negative profitability. Margin return on marketing investment -0,4 showed us that Econea was losing EUR 0,4 in profit for every 1 EUR invested.
The comparison of mROMI in Markov and last-touch attribution model.
This fact was not acceptable. Criteo, as the remarketing platform standing at the end of conversion path (a fact confirmed by ROIVENUETM path analysis) should not have negative profitability.
Path and analysis of marketing channels.
Econea was able to act on those findings and decrease bidding in the platform. These changes then resulted in savings in investment and again in an increase of the overall effectiveness of Criteo. Criteo turned to positive ROI and was showing increasing marketing profit for the last 3 weeks as of writing of this case study.
Marketing profit from Criteo is positive.
Thanks to ROIVENUETM data integration and attribution products Econea made the leap to data-driven company.
“ I think that cooperation with ROIVENUETM it is a huge step forward and we can see that hard work in weekly evaluation of marketing activities and data-driven decisions based on data we can trust are paying-off. However, there is still quite a lot ahead of us.”
Martin Lanta, Econea's CMO
All and all, the margin return on marketing investment (mROMI) in the last month increased from average 1,6 to 2,3 mROMI - meaning that Econea increased its profitability by 40%. Thanks to the optimizations initiated by Martin Lanta, Econea was able to save money and it is planning to reinvest them in an upcoming brand campaign that will support the future growth of this beloved brand.
Overall business mROMI is growing.