Alpine IQ analysis page breakdown – AIQ

We make it easy to find impactful business drivers using a single consolidated analysis view. Below we go into detail of what is available as of 6–17–2020 in the Alpine IQ Retail Platform. If you enjoy our insider articles please follow our blog and give this post a clap at the bottom of the page.

1.) Geo insights
Provides you with a global view of customers for your selected audience, brand, company, or enterprise. The map generally has a heat map of customer locations as well as relevant retail locations. When zoomed in, the map will have zones color-coded for common geo-restricted areas such as schools, public transport, e-sports complexes. Customers use this insights page to discover potential M&A targets, licensing opportunities, locations for legal promotion of goods, and much more.

2.) Demographic insights
Contains breakdowns for gender, age, race, income, and housing in percentages based on what is selected.

Demographic sampling based on your customers avg. market area center point.

3.) Order insights
An overview of analytics related to orders made via e-commerce or in-store transactions.

Total orders
Avg. order checkout price
Avg. cart items per order
Avg. days between customer visits
Number of orders by product category
Number of orders by brand
Number of orders by payment type
Top 20 purchased SKU’s across all orders
Orders by day of the week
Orders by month
Top performing products by category

4.) Predictive analytics
Machine learning derived insights related to orders and geo signals.

Predicted purchase frequency
Predicted order value
Predicted customer lifetime value over 3 years
Net CLV based on actual margin
Maximum ideal customer acquisition cost
Maximum CAC with margin taken into account (Uses 1/3rd rule)
Likely to return to the store soon (Tells you what percentage of users in an audience who are within 30% of the median time between store visits.)
Likely to be in top 20% of spenders (Percentage of audience members that are in the top 20th percentile of customers based on order history)
Predicted top X (Looks at current users purchases or cart history and predicts SKU pairings/ brands/ and categories a user will buy next.)

Sample of predictions made for this audience based on custom machine learning models.

5.) Event analytics
Your custom tracking pushes and occurrences for each key/label

6.) Action analytics
Actions are engagements or “events” your destinations track on your audiences. Conversions are orders made by personas either online or in-store that can be linked to an action from a destination in the last 30 days. When attributing a conversion, we assign it to the last destination that there was an action generated for a persona.