personalized experiences can improve the ROI

Recent statistics show that brands need to offer more personal customer experiences.

• 80% of consumers are more inclined to buy from brands that offer tailored experiences.
• 70% consumers believe that a brand’s ability to understand their needs and build loyalty is key.
• 71% customers get frustrated when they don’t have personal experiences.

All of this may be true. However, it can be difficult to calculate the return on investment required to create one-to-one experiences. It can take many months and millions of dollars to achieve this goal.

This three-part series will examine how marketers can measure their performance and return on personalized customer experiences. I will also address several questions organizations should ask before embarking upon a large-scale project.

Let’s begin our discussion about measuring personalized customer experiences by focusing only on one aspect — the customer. Personalization is measured by audience performance. This means we measure both individuals and groups and their reactions to tailored content, offers, and journeys.

This article will discuss different approaches to audiences and personalization. I’ll also address the skeptical views surrounding the return on one-to-1 personalization’s effectiveness.

Personalization is only possible when you understand your audience.

We have all received text messages or emails saying the same thing: “Hey [insert name here], would your like to get 50% off [insert service or product here]?”

This is what some might call “personalization,” because you were able to insert your name instead of saying “Hello, random person.” However, this is not the kind of personalized experience I want.

Let’s call this approach “substitution” instead of “personalization”, and let’s focus on stronger examples and better ideas.

We need to know more about our potential customers and customers than their first and last names, email addresses, or phone numbers in order to do anything other than simple substitution.

The first party data strategy is why you will see many brands investing in tools such as customer information platforms (CDPs), and even second-party platforms that pool customer details among trusted parties. Major technology companies are removing third party cookies and tracking mobile device IDs. This strategy is vital.

Let me ask you a question: If personalization is dependent on your understanding of your customers, how can you be sure you are doing that?

It is essential to create a first-party information strategy and infrastructure that allows you to develop customer profiles , and then evolve their information over the years.

It is necessary to create a strategy for first-party data:

• The right infrastructure (e.g. CDPs and CMSs).
• Customers who trust you with their data.
• This data can be used to continuously enrich and provide personalized services to customers.

Get deeper: What’s personalized marketing?

Personalization lift requires understanding relative measurements

This one is for all the personalization skeptics. Without a real experiment, how can you determine if personalization works? It’s not very easy, actually!

A relative measurement can give you many insights into how personalization works (or not). You’ve likely seen it before:

• You can show a customer exactly what product they purchased by using imagery on the website and an email.
• Show the customer the product you customized during your last visit.
• You can customize the imagery that is displayed to customers based on their location or other demographics.

Next, show them a generic product, or another one-size-fits all text or imagery. Although you may notice a lift in certain areas, this is part and parcel of the benefit of using relative measurements.

It is important to understand the key levers that create the most value, as creating customized content, offers, and experiences requires more resources than a one size fits all approach.

You may one day be able personalize everything on every channel. However, it is important to identify the most impactful aspects so that you can make improvements without wasting resources.

Get deeper: How do you humanize digital experiences with first-party information

The ultimate measure is CLV

There are many useful metrics that can be used to measure the effectiveness of personalized experiences. However, they can also be difficult to use. Customer lifetime worth (CLV), requires both extensive information about the individual’s actions and perhaps the most valuable commodity of all: time.

CLV can be used to measure the impact of a personalized, comprehensive customer experience on buying decisions and service usage. It includes the cost of acquiring a customer which can sometimes be an investment to convert them, and then shows how one customer can drive long-term value.

This is because of the time-based component. If a customer’s average life expectancy is five years or more:

• How can you quickly get a CLV model that is useful?
• How do you know what role personalization plays within this model?

There are many models that can be used to calculate customer lifetime value. However, they will still use historical data to generate averages for spend over time, churn, and other factors. These can be used as baseline measurements.

You can also use relative measurements to determine the impact on customer lifetime value of customers who received less personal experiences than those who were younger customers who might have benefited more from personalized experiences.

Multi-touch attribution will be covered in a future article. However, being able to attribute conversions and value to specific interactions and channels can help you answer a question about personalization’s value in the overall CLV.

What amount of personalization is sufficient?

Apart from the fact that personalization is a good way to influence buying behavior for marketers, consumers appreciate personalized experiences.

Personalization can come at a cost to both the brand (which may be passed on to customers) as well as to the amount we share with others (which could affect our privacy). The question is, how much personalization should you allow? Is too personalization possible?

There are many ways to view this.

• If the systems and processes aren’t designed to deal with the increased demands, personalization can quickly drain internal resources.
• True personalization requires AI and machine learning models as well as predictive analysis. These models can be very effective but require time and training.

Perhaps it is better to ask how personalization is sufficient, rather than asking:

• What level of personalization can you use to make improvements now
• What are the best things to do for the future?

This approach allows customers to benefit from a customized experience, while your infrastructure and internal teams adapt to these changes.

It is easy to measure the ROI of personalized content, offers, and experiences if you pay close attention to these aspects.

The post The ROI personalized experiences: Audience measurement was first published on MarTech.