How customer duplicate merges work

Alpine IQ performs merges to avoid customers having duplicate loyalty wallets, missing points, and to get accurate historical data for actionable use cases in marketing/ analytics. i.e: if you only have a small view of the customers history, you will not have accurate avg. basket values, lifecycle stages, favorite products, etc. The entire customer journey requires cleansed data to maximize revenue and build a quality customer relationship. You have maximum control over how you wish for your data to be merged and synced but by default Alpine IQ uses our battle tested process across over 1200+ retail ops and over 50+ cannabis specific integrations controlling 191,903,881 cannabis customer records as of 9/3/21.

Merging is only as powerful as your data. If your staff is putting in fake data, your merging is going to be very difficult to resolve. It is impossible for Alpine IQ to know every possible fake data entry but we do automatically define possible fakes after we notice a high percentile of non-matching users leveraging the same email/ phone etc. i.e: Staff asks for customers phone but to save time they enter 888-888-8888 or email as no@gmail.com/ 1234@gmail.com etc. Please train employees to NOT do this. If the customer does not want to give you information, do not put in fake data.

Common reasons for merges

• When a customer updates their contact info via 1 source of data (Mailchimp, AIQ forms, your website, e-comm checkout, etc.), Alpine can merge that new user data into a master profile and sync it across your entire marketing and data tech stack.
• If you own franchises or have splits with branding across states or provinces. AIQ can sync certain duplicates only within certain territories across multiple POS systems and other tools in your tech stack.
• Household accounts get merged so that they can access their combined points/ discounts (Common with spouses)
• Merging can combat fraud and users trying to game advanced drip campaigns or strategies. i.e: Customer signs up 100 times to gain access to a points boost you might setup more than they should. Customer refers friends under different accounts because the first referred friend gives you more points than repeat referred friends. Again this is all dependent on how you customize your AIQ setup but

What we merge on and why

For reference, Alpine only uses deterministic matching to merge customers. We cannot due to compliance, merge customers with shared attributes such as birthday or name (Probabilistic). The most common merges happen do to matches on the following user data:

• Customer Phone
• Customer Email
• Customer Gov ID number
• Customer MED ID number

How to search, view, revert, or modify a user for expected merge behavior

• To search for a number or email of someone who you think may have been merged, you can use this merge search function. merge: Here are some examples below.

• You can view what merges have occurred for a customer under the left nav "Personas" page. Choose a customer you wish to view in the table by hitting "View" next to their name. Navigate to the "Merges" tab at the top of the slide-out panel. If you do not see a merges tab, the customer has no merges at this time.

You can modify a merge a few ways:

1. Change their customer details in the POS or natively in the data source the profile comes from (CSV uploaded, Email provider, etc.). (Note: Editing in the POS would not change what is in AlpineIQ until that personas next purchase)
2. You can change the master customer details within AIQ. Click "Edit contact" under the "Traits" tab shown in the above screenshot on the view persona slide-out. This method will modify the data across all of the merges that have already taken place.
3. If you would like to remove a specific merge from a customer, first navigate to the merges tab shown above, then click on the platform/ merge listed that you would like to modify. Required fields will vary by merge. Changing details within a specific merge will cause the merge to back into record linkage processes. This user could be matched with new data that is relevant. The most common use case for this method is to remove a bad merge because of bad data entry. This allows you to manually split the bad merge away and allow it to naturally process correctly with historical + future data ingested.

What happens when you modify a user that was merged deep dive

There are a number of situations in which dirty-data can cause unwanted merges, and in turn cause spikes or severe dips in a persona's points balances when unmerged. Some edge case scenarios below: - John Doe is merged with Jill Smith due to a matching phone number in their POS system. In AlpineIQ, their sales and points have also been merged together. John has been redeeming discounts and using points for the combined persona. A staff member then realizes that Jill's phone number is incorrect in the POS and goes in to correct it. This would cause John and Jill to un-merge and have 2 separate profiles. Given that John has already been redeeming discounts and points all this time, and he no longer has Jill's sales being included in his persona, his point balance falls to 0 (because he now only has redemptions under his persona and none of Jill's sales accruing him points). Jill, on the other hand, would see a significant spike in her points because the redemptions John made in their merged persona are no longer present, but the sales (and the point accruals are). - Ben Smith is a loyalty member with a phone 123-123-1234. He has spent $500, has 500 points, and has just made a discount redemption for 100 points. His balance is currently 400 points. An existing customer named Amy shows up in store. She has $1000 worth of purchases and thus 1000 points. The staff member decides to update her phone to 123-123-1234 in the POS. This causes her profile to now merge with Ben's because he also has the same phone. Ben's balance updates to 1400 points because Amy's orders are now merged with Ben's.

Take aways:

1. 99% of the time you will update a customer by going to view the persona in Alpine IQ, then clicking "Edit contact" at the top of the slide-out traits panel. All merged accounts will update to be the newly edited contact.
2. If you would like to split off a merged user to their own profile, and you are ok with points being recalculated do to a scenario above, you will do so by altering the merged record under the "merges" tab. This will spit that record away without touching any other merged records.
3. Please train your staff to NOT put in placeholder data or fake entries for your main merging fields (Phone, email, Gov ID, Med ID)

Why do points not match dollars spent in the personas slide-out sometimes

1. If the customer was given a gift/ boost/ multiplier on points, "spent" will not line up with points accrued.
2. If you run a specific loyalty accrual setup such as "1 point per $ spent" and then at a later date decide to update your accrual to be something else org wide, it could cause users to fall into negative points after recalculating your points ledger based on the new settings, assuming they had already redeemed discounts with the previous methodology.
3. In the above scenario, John's points are taken to 0. This is because we do not take them to negative points balance. 99% of unmerges are simple mistakes made by staff or old data files. If John's profile is split off, Alpine IQ will take him to 0 points and log a "block adjustment" for the amount of points he went negative. This is to not punish a user for something that is not their fault. Instead, they can go to the store and start accruing on their new profile from 0 points instead of negative points.

How long it takes to modify merges

• When updating via a connected source (i.e changing phone number within a POS), merging will not happen until that source of data is synced again, or for POSs until the persona you have modified makes a new purchase.
• When updating via the Alpine IQ dashboard, merge modifications will typically reflect the following day, after the data sync has been completed.