ORANGE TELCOM AND DIGILINE DOUBLE REVENUE FROM BRAND CAMPAIGNS WHILE RETAINING ROAS THANKS TO IMPRESSION LEVEL ATTRIBUTION

Category: Case Studies

Orange Telcom and Digiline

double revenue from brand

campaigns while retaining

ROAS thanks to impression

level attribution

  • All clicks and impressions from brand campaigns

were incorporated in the customer journey.

  • Algorithmic attribution revealed enormous

differences in ROAS of the same campaigns ran across

different placements.

  • Well performing placements were reinforced and

budgets were cut down on the worse performing ones.

  • 100% new sales revenue was brought in while

retaining the same ROAS.

The Challenge

Orange (#1 Telco in Slovakia) and its media house Digiline had been running brand awareness campaigns in the form of pre-rolls,

skin formats, and videos for several years.

 

The problem had always been knowing which placements are the most effective in bringing in sales and contracts. Through the

traditional measurement methods based on the last click data or through a post-click window neither the agency nor the client

had been able to determine which placement is better. That in turn lead to a conservative strategy which lead on to overspending

on channels that would favour the last-click attribution.

 

The challenge was then in integrating the right technologies to provide new insights about the true ROI of their advertising

Euros that meaningful action could then be taken on.

 

 

The Solution

MEASUREMENT

 

​Knowing that measurement of clicks wouldn’t get us far, Roivenue and Digiline worked closely together on the implementation

of impression level measurement through a combination of Google Analytics, Gemius and Roivenue Data-Driven Attribution Suite.

 

Five different goals with the correct revenue value were configured in Google Analytics to include all conversions Orange considers

valuable ranging from direct webstore orders to a successful use of a store locator.

 

Gemius Direct Effect and Gemius Prism tools were used to tag every delivered impression with a unique ad ID.

 

All data was then passed to ROIVENUE™ where conversion paths (including impressions) for all users were reconstructed. The

suite then calculated algorithmic attribution results and true ROAS for each placement.

 

If users who saw ads on one placement were converting more down the road, it meant the ROAS on that placement were higher.

 

The analysis showed that there really was a significant difference in the performance of different placements ranging from

ROMI 0,9 to ROMI 14,0 (!) with an average ROAS of 5,4.

 

Impression based attribution thus showed that there really was up to 16x difference in performance of different placements

– something that couldn’t have been discovered using the previous measurement stack.

 

 

 

OPTIMIZATION

 

​The next step was optimization.

The goal for the upcoming season was to maintain the ROAS at a higher level of investment.

 

Luckily, with the knowledge of true ROAS, the budgets could be spread in a much smarter way than simply doubling everything.

The great performing placements receive more than double of the previous budget while the not so good performing ones were

cut down on (even though the overall budget was doubled).

 

ROIVENUE™ dashboards allowed Digiline Media house to shift budgets from worse performing placements to the ones with

higher ROAS, and to do so on the fly based on the fresh results every week.

 

 

 

Results 

With a smarter budget redistribution among different placements, Orange and Digline were able to double sales revenue with the

same ROAS.


“Thanks to the impression level attribution, we found out that different ad

placements had dramatically different ROAS down the road. Based on that

we were able to distribute our budget more effectively. In most cases,

performance usually goes down with increased budgets as audiences get

saturated with the message. With ROIVENUE™, we are finally able to find

the best performing placements and continuously optimize for the best results. “

 

Matus Kristofik, Knowledge Manager, Digiline