Case Study: Offline promotion of Digital goods

Objective

The document represents a case study for the “Dynamically Served Digital OOH” format for Grabb-IT. Grabb-IT has built a Video/Display advertising format that is delivered on a ride-sharing vehicle allowing the Ads to be hyper targeted (Hyper Local + Time Parted) with precision

Goals

The case study is trying to prove;

  1. The DD-OOH format delivery creates a very high brand recall
  2. After viewing the ad delivered via DD-OOH, users tend to have a significant purchase intent

For the case study, Grabb-it partnered an innovative startup e-commerce company delivering customized greeting card targeted for Valentine’s day. The brand for this company was relatively new and that helped creating a better study environment.

Method

To deliver the case study, two high foot density locations were chosen that have repeat footsteps to test brand recall;

  1. A one-week campaign at two locations in California
  2. 5 Cars; 12:00pm – 2:00pm & 5:00pm – 8:00pm across downtown Mountain View, CA
  3. 3 Cars; 4:30pm – 7:30pm at Local BART Train Station, Fremont, CA
  4. Surveyors randomly intercepted people on last day of campaign on side walk and asked survey questions (sample responses)

The method was developed making an assumption that consumers were coming back to the same locations;

  • Downtown Mountain View targets users between 12-2 that are office goers nearby
  • Downtown Mountain View targets users between 5-8 that live nearby
  • Most commuters from the city coming back to Fremont come back between 4:30-7:30 PM

The e-Commerce greeting card company chose these locations targeting affluent millennials that were busy in their life and agreed to the two locations as a good test.

From a Grabb-IT perspective, these locations were interesting because it would be very hard to bring promotions to these areas – they are thickly populated (or regulated in the train stations case) and without Grabb-It it would be hard to promote users.

Another basis was catching the users in the right moments but very hard to measure;

  • In downtown Mountain View, the idea was to target consumers about to make decisions (about food or places to go)
  • At the Fremont BART stations, the idea was to target leisure consumers who were completing the productive cycle of the day

The Creative

The creative was a full 30 second TV slot that was posted on a rear window of a ride sharing vehicle. The creative repeated itself with a small pause allowing passer by footsteps to see a full LCD quality TV ad right where they were making decisions.

The TV creative was provided by the digital greeting card company based on their TV and Video digital ad strategy.

We are unable to share the final creative for now, but here is another test creative for Grabb-It to help understand how the creative worked.

 

The footstep engagement gives you a perspective of the potential of an innovative ad unit that can be deployed to hyper targeted areas.

Results

The results were calculated based on 100 surveyors a week after the campaign based on assumption of repeat footsteps.results

What the above results told us were;

  1. 45 out of 100 remembered seeing the digital greeting card advertisement
  2. 95% (43) of those 45 recalled the brand (digital greeting card company)
  3. 60% (28) of those understood the brand product
  4. 47% (22) of those were willing to make a purchase of the product

The above results significantly outperform digital advertising and OOH purely based on the hyper-targeted aspects. To provide a comparative note;

comparison

What we were able to prove was Digital OOH converging digital and OOH for hyper targeting outperforms existing formats by 20X.

Conclusion

In conclusion, what we were able to prove was;

  • Grabb-It was able to reach in areas that reached affluent millennials with the right mindset where digital advertising or OOH would find it hard to reach
  • Grabb-It outperforms traditional advertising by 20X in brand recall metrics
  • Grabb-It was able to create a purchase intent of about 20% within exposed groups which is significant

With new technology, and innovation the measurement methods for Grabb-It will significantly improve where advertisements can be mapped back to purchase cycles soon. However, with this study we were clearly able to prove that Digital OOH via ride-sharing cars is here to stay.

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