Create a Customer Journey Map in 4 Steps
The goal then is to reach the recipient at exactly the right time, when they are more open and receptive to our communications. To do this, you need to get to know their movements, preferences and identity inside out.
From developing integrations to strategic support, from creating creative concepts to optimizing results.
Who are they? What (digital) route do they take to get information, news or tips? Which channels do they use, and how? In short, it is important to thoroughly profile and segment your database.
Why create a customer journey map
In recent years, the customer journey has definitely changed and is continuing to evolve at an extremely fast pace. In a very short space of time, we have gone from linear buying behavior to extremely complex behavior through dozens of communication channels (places where we consume information) and devices (tools through which information comes to us like desktops, cellphones, smart TVs or smartwatches).
Each point of contact between the user and the brand is known as a touch point: it is paramount for the company to know all its touch points, map them out and manage them.
How do we unravel this and make sure we’re sending truly relevant communications? We need:
- To intercept users who have shown an interest in buying a particular product through their behavior and previous purchases (profiling)
- Send these users an ad hoc message (segmentation)
It seems easy, but it’s not. Let’s look at a practical example.
1. Type of e-commerce: Beauty products
2. Promoting: Anti-aging creams for women
3. Tool: Newsletter
According to ‘traditional’ marketing, we could perform a segmentation based on “gender: women”. It’s better than nothing, but it’s not enough. The message is not relevant for the following reasons:
- Insufficient segregation: a 20-year-old woman is unlikely to be interested in an anti-aging product that may even be expensive. It should be further segmented by age, average sales receipt, etc.
- Off-target segmentation: A 20-year-old man (hence completely off-target) may need to give a present to his mother and so shows an interest in the anti-aging product when browsing the website.
So before starting any Marketing Automation project, it’s crucial to invest the right amount of time and budget into:
- Mapping out the touch points between the customer and company
- Analyzing the interaction between the user and each of these touch points
- Using them to set objectives and KPIs for marketing
- Integrating the data collected and performing profiling
How to design a customer journey map
1. Determine the touch points between the customer and the company
There are various touch points between the customer and the company, which means they must be identified and carefully mapped out:
Broadly speaking, every business knows what the main touch points are with their users. However, it’s often the case that some touch points escape them and are not managed properly, resulting in lost opportunities to establish a fruitful dialogue with the potential customer.
2. Establish the mode of interaction between the user and touch point
Ok, we know what the touch points are. But how do users behave in relation to each of them?
- How much time do they spend on each touch point?
- What actions do they perform?
- What is the goal of their interactions?
3. Set goals and KPIs
Once you’ve finished your map, it is important to set objectives and KPIs (performance indicators) based on the user’s mode of interaction with each individual touch point. For example, for websites the focus is on user browsing and shopping; for social media the focus is on user/brand/competition interactions; for offline it is on buying behavior, etc. So, purely by way of example:
- Website: objective is traffic, KPI is visits
- Social media: objective is engagement, KPI is interactions
- Events: objective is awareness, KPI is participants
- Promotional DEMs: objective is conversions, KPI is number of orders
And so on.
Integrating the data collected, from mapping to profiling
Mapping touch points and setting objectives and KPIs for each of them is still not enough. We have to make the collected data “interact” with each other to remove the user’s anonymity and create a unique “identity card”.
What do we know about our users? First of all, we have a unique identity card for each user, which allows us to trace their behavior on the company’s touch points. It’s now possible to profile every identity in database based on demographic and behavioral data.
There are two main types of data that we access: demographic data (i.e. relating to ‘static’ user information) and behavioral data.
This is the classic information used to create the traditional buyer personas. These include:
- First name
- Last name
And so on. This is essential information when performing a segmentation based on geography or personal details, but it should also be integrated with information on behavior. As pointed out earlier, a 20-year-old male wanting to give his mother an anti-aging cream is a high potential client who would not have been intercepted by demographic segmentation alone.
This is the data collected by analyzing the interaction between the user and touch points, which accurately outlines the user’s behavior, interests and attitudes based on facts, rather than theoretical data. This information includes:
1) Frequency of purchase:
- Frequent buyer
- Sporadic buyer
- VIP buyer
- Loyal buyer
2) Recency, i.e. the last date of interaction:
- Active user
3) Purchase date:
- Average sales receipt
- Medium shopping cart
- Most purchased categories and products
4) Mode of interaction with the various touch points:
- Channels (SMS, website, email, etc.)
- Device (mobile, desk, tablet)
- Social network
- Live chat
Coming back to the example of the e-commerce selling beauty products, this way we can now broaden our targets not only to static segments extrapolated with quantitative data (e.g. women over the age of 60 who already purchased an anti-aging product 6 months ago). We can send unique communications even to 20-year old men (demographic data) who may have seen the anti-aging product category and used the live chat to find out which is the best product for women over the age of 60 (interaction with company touch points) and who are regular buyers (frequency).