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.
- geo targeting / geo fencing
- redemption / purchase in a store
Today, there are lots of moving parts, which makes it look a lot like Swiss Cheese.
- estimote (beacons)
- RetailNext (wifi analytics)
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
What do YOU think? Let me know...