We’ve broken them into three main categories:
- Visitor personalization: personalizations based on the specific visitor
- User personalization: personalizations based on the specific person
- AI / aggregate personalization: personalizations that are a best guess of what a specific person wants, based on aggregate analysis of what other customers and users did.
Visitor Personalization
1. Personalize offers based on location
Show visitors what’s currently available near them based on their IP address or self-selected location. You can also show visitors what’s trending near them, or personalize your offering based on where they are in other ways, like showing products related to the weather, a sporting event, etc...
2. Personalize based on previous visits
Have they visited your web store before? If so, you can tailor both how your web store functions as well as what they see first. For example, can you highlight products they were looking at before but didn’t purchase? Or can you highlight not those same products but comparable products or product alternatives? For example, if they were looking at a pair of running shoes, maybe you can show them running socks.
3. Personalize your remarketing
If you have a visitor to your site, can you cookie them and retarget them with personalized ads? Can you show price drops around the product category they were looking at, product alternatives, or other relevant offers in other channels like social media?
User Personalization
These personalizations are for when you know the actual customer who’s in your store — e.g. they've logged in, or given their email and you know who they are.
4. Personalize based on previous shopping patterns
Do you sell a product that gets purchased cyclically (e.g. consumable products like food or makeup). If so, then can you track a customer’s buying cycle and personalize your offer around their needs?
5. Personalize additional product recommendations
Taking the same dataset as above (e.g. their purchase history) and offer specific products that pair well with what they’ve bought. For example, if you were a grocery store, you might offer a discount on salsa to people who purchased tortilla chips.
6. Personalize future product based on who they are
As you learn more about your user, you can start to understand them beyond your own store. Are there life events you can predict, or other forces that would drive buying behaviour? If so, then you can leverage that information to offer the correct product and message at the right time.
7. Personalize your channel communication to match the buying stage
This one is a little complex. First, we need to understand there are different levels of buyer engagement, usually aligned to awareness, consideration, and evaluation. Now, if you understand a specific user’s path to purchase, then you can customize your channel communication to that specific user so that messages in the channel match the level of buyer engagement.
For example, say that you have a customer who always purchases through your email newsletter. That means the stage of engagement for email for that person is evaluation — when they’re reading the email, they’re already primed to buy. So you should focus their version of the email on late-stage offers — discounts, BOGOs, etc…
Other channels that this person engages with should not include those offers, since they’re clearly not what this person is thinking about. For instance, if you’re serving them Instagram ads, you should aim to build product and catalogue awareness, rather than convince them to buy that product from that channel (since it hasn’t worked in the past).
You’ll end up with a table that looks like this:
