Harnessing the Power of Intent Data and Predictive Analytics
Michael Mire, SweetIQ
Local search is the ultimate indicator of intent.
- We’re doing it all the time. (4 in 5 consumers use search engines to find local information.)
- We’re doing it more and more. (Google search interest in “near me” has increased 34x since 2011.)
We’re on our way to online to offline (O2O) direct attribution.
Today, there are lots of moving parts, which makes it look a lot like Swiss Cheese.
You’re only able to track <3% of the market today, so it’s difficult to create a reliable model.
Build an O2O attribution funnel / model.
- Impressions – number of times your stores appeared in local search
- Local Search Behaviors (LSB) – amount of website referrals, calls, and driving direction requests (microtransactions)
- Conversions – percentage of click throughs that result in an online visit or an in-store visit.
- Sales – percentage of conversions that actually result in sales
O2O sales mimic online results.
Step 1 – monitor LSBs
- beaconing (in the future…)
- Finding a Local Listing -> see and go!
- Click for call
- Click for directions
- Leave reviews
- Mobile/Geo-targetd Ads
Step 2: Track in-store conversions
- 68% connected with the business
- 71% visited the business
- 18% purchased
Step 3: Know your average purchase value
Know what the average visit in store converts to.
Step 4: Track the performance over time
The model may not be perfect, but if you can track over time, you can see
Step 5: Calculate your local revenue
Step 6: Calculate Local ROI
ROI = Local Revenue / Program Investment
Case Study – Chuck E. Cheese
Local Search Behaviors
Online to Offline Attribution Model
Impressions – Local Search Behaviors – Conversions – Sales
Target ads based on location