Is There a Formula to Estimate the Upside of Personalization?

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In the previous two entries in this series (Part 1 here and Part 2 here), we explored the source of many of the commonly-used statistics that attempt to assess the potential upside of AI-driven personalization, and then went deep into what experts have said more recently.

After reviewing numerous sources, it seems there is still some work to be done to help companies set realistic expectations about the impact personalization can have on their businesses.  How specifically might one go about estimating the potential upside in specific categories and circumstances?  This is not an easy question to answer. (I thought this would be Part 3 in the series, but given the complexity, think it makes sense to split into Part 3a and Part 3b, to follow.) The analysis below and in Part 3b gets somewhat involved, but it is worth working through to the end.

We can use AI itself to give us a start at answering the above question with a query like this: “How can you use AI-driven personalization to increase customer value”? Here is what Gemini responded:

Personalization increases customer value by tailoring experiences, content, and offers to individual customer needs and preferences, making them feel valued and understood, which leads to higher engagement, loyalty, and ultimately, increased sales and customer lifetime value; this can be achieved by leveraging customer data to deliver relevant product recommendations, targeted promotions, customized support, and personalized content across various touchpoints like email, website, and social media.

So “…tailoring experiences, content, and offers…” will lead to “…higher engagement, loyalty, and ultimately, increased sales and customer lifetime value”.  Sounds like a recipe for success, if done effectively.

Next, we can apply the components of that response against three broad approaches to how companies can achieve growth:

1. Acquire new customers: Personalization might entice more customers to enter a category than otherwise, because the personalized messaging awakens a need that might have remained dormant, or offers incentives that overcome barriers to purchase.  Similarly, it might encourage switching from a competitive brand because the messaging and offers sway decision making.
2. Retain existing customers and encourage them to increase their levels of spend on currently-purchased products and services: Personalization entices current customers not only to continue their current purchase patterns, but also to buy more frequently or spend more by anticipating needs and wants with timely and relevant messaging and incentives.
3. Encourage existing customers to purchase additional products and services: Personalization leverages knowledge from current customer purchases of adjacent products to tailor appeals and anticipate buying needs for new products.

From this, you can easily collate a laundry list of “what to do’s” with regards to personalization, that might include:

• Create segments and deliver targeted messaging and offers relevant to each segment, down to segments of one
• Suggest products most likely to be of interest to individual consumers based on past purchases or browsing activity and other intent signals
• Utilize dynamic content and pricing on websites to personalize page content, product recommendations, CTAs, and more
• Provide proactive customer service by arming CSRs with detailed customer knowledge and suggestions for optimizing each interaction
• Pre-populate individualized data to make transactions more seamless
• Utilize personalized loyalty programs to create incentives and deliver offers that are unique to each member

One immediate concern comes to mind: this list simply describes potential tactics from a brand’s perspective, and we still don’t have a sense of what impact all of this work could potentially have on our three growth levers. So we need to also consider the relevant factors that typically impact consumer brand selection and spend on a product or service.  Here are three that directly impact how much a consumer spends and on which brands:

1. Frequency of usage. Can consumption be expanded?  Is that by taking consumption occasions from a substitute or competitor, or by truly adding incremental usage?  You can certainly expand consumption of soft drinks, for example, but maybe not toothpaste.  And less likely for more need-based purchases, for instance, underwear or consumer durables.
2. Quantity consumed per occasion. Similarly, can consumption be expanded with each use?  Again, definitely for soft drinks, unlikely for toothpaste.
3. Category purchase concentration. This refers to how much category spend a consumer concentrates on a single brand, sort of a proxy for brand loyalty.  What is the likelihood a consumer will be open to switching preferred brands for a given purchase occasion?  For soft drinks, this might be higher than for other categories because of availability issues, and consumers may consider many brands to be acceptable substitutes due to low loyalty or a need for variety.  For toothpaste, this might be lower because consumers may tend to focus primarily on a particular brand, and only switch based on dramatic price differences or issues with availability of their preferred brand.

Combining these thought lines, we can suggest that the upside of personalization for a specific brand is a function of these factors:

• Category growth rate
• Frequency of product purchase/usage
• Degree to which consumption can be expanded on a given occasion
• Likelihood to switch brands on a given purchase occasion, which can potentially be represented by highest spend concentration on a single brand
• Personalization leadership/sophistication

In Part 3b, we will attempt to develop a working formula based on these factors.

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