Word on the street is that customer intelligence is the next step for maturing your marketing.
You've probably heard the word on the street about the newest form of transforming customer data: Customer Intelligence.
Customer intelligence takes the data from analytics and creates actionable business insight that you can apply directly to your strategy.
But being the skeptical person that you are, you might be asking yourself: What is customer intelligence exactly. And what is its value?
When you enter into the more abstract territory of justifying costs that help you reach quantifiable results (e.g., increased incremental revenue, higher conversion rates, etc.), it can be challenging to wrap your head around the indirect impact fully.
To help clear the air on the real value of customer intelligence, we’ll walk you through some of the game-changing benefits of this investment.
Customer intelligence is what makes customer analytics actionable. By leveraging AI it allows you to process customer data to understand and build deeper relationships with your customers.
It gives you insights that create a clearer view of your audience so you can provide them with more relevant communication that facilitates the decision-making process.
This data can be collected in various ways but let’s quickly cover the most common methods:
Raise your hand if you have customer personas.
Everyone? Thought so.
I’m willing to bet that you created these initially based on a combination of guesswork then validation through some kind of interview format. This qualitative approach is among the most popular, as it’s the first touch point in understanding your target audience on a more personal level.
These interviews can be a great starting point for defining your customer. However, it’s not always the best tool to really understand them because it's difficult to scale and individuals can give socially desirable answers.
So let’s move onto some more effective approaches.
Surveys can be a great way of obtaining customer data with a bit more volume than is possible with interviews and groups.
Especially when you hire a market research firm with a broad network. Or use more natural "conversational forms" like those of Typeform.
These surveys are effective at measuring the explicit beliefs, intentions, and motivations of your audience. By explicit, I mean that answers that we consciously think about. These decisions are also referred to as System 2 decisions for those of you who may have read Daniel Kahneman’s Thinking, Fast and Slow.
Explicit thoughts and decisions make up approximately 20% of the choices made on a daily basis. Meaning that there can be a pretty large gap between what people think they will do and what they actually do.
For this reason, it’s essential to follow up any interviews or surveys with research methods that collect real-time behavioral data.
A more precise way to collect customer intelligence is by sifting through your website’s behavioral data. Analyzing this data can give you insight into the bottlenecks your website visitors’ might be experiencing that are preventing conversion.
However, where the real goldmine of behavioral data tracking is when you run experiments on your website. When doing this, behavioral data can be the key to learning about the motivations and behavioral tendencies of your audience.
By running experiments on your webshop, you can test how your visitors respond to different subconscious triggers like CTA colors, pricing, or persuasive messages.
But why would you want to use “subconscious triggers?”
Well, these can help you determine how your target audience makes decisions and the psychological triggers that initiate their behavior. By collecting the resulting experimental data, you can segment your target audience and make various customer profiles so you can personalize the customer experience on a micro level.
Check out this blog post for a step-by-step guide to setting up experiments to collect these data profiles.
After conducting the necessary customer research, you should have various data points that represent your target audience and the multiple profiles (or personas) that fit within it.
To turn data into intelligence, you need to integrate the various points into a greater context. For example, you may have the following data points from several hundred visitors:
When translated into customer intelligence, it might look something like this:
Website visitors in London that are coming from Facebook on an iPhone (Chrome) respond positively to social proof messaging when faced with choice overload on the product listing page. Individuals who respond to social proof generally look to others in times of uncertainty to help themselves to make a decision.
This segment is also motivated by excess demand scarcity messaging on the product detail page. This tendency prompts users to act decisively out of fear of missing out on buying the selected product.
With this, you’ve created a new segment that can be tested in other channels.
When it comes down to it, the drive behind customer intelligence is to gain a 360-view of your customers so you can create unified profiles that incorporate all your customers’ data.
For online retail, this information is especially interesting for increasing conversion (acquisition, order value, and upsell) and effective omnichannel marketing.
So, to take this one step further, you can turn this intelligence into insight. Customer intelligence insights can be used to improve the relevancy of the customer experience, ensuring that your messages resonate with their audience.
From the description above, you can implement this into your communication by using social proof/excess demand scarcity message on that segment. For example, a Facebook ad campaign can be created using a mix of social proof and scarcity.
Customer intelligence provides the context in which purchase decisions are made so you can apply the insight omnichannel to increase conversion.
To get the most out of customer intelligence, you will likely need a system that can store the information. To do this, most companies will go for a Customer Relationship Manager (CRM), Data Management Platform (DMT), or a Customer Data Platform (CDP).
These three systems serve different purposes, so whichever you go with largely depends on the industry, department, and needs.
CRM systems are generally used to monitor the business relationship with individual customers. In the retail industry, these are primarily used to track transactions and customer communication.
It uses this information to understand who purchased which products, when they were obtained, and the process they went to buy them. Because of this, it can be used to streamline marketing automation to existing customers.
Unfortunately, however, CRMs aren’t generally able to process large volumes of data from multiple sources, making it not an ideal platform for storing customer intelligence.
Although many may confuse DMPs with CDPs, which is understandable as they seem quite synonymous, they are structurally different.
DMPs are designed to serve advertisements and retargeting campaigns with the use of a cookie. The profiles saved within this system remain anonymous, making it more difficult to target specific users.
Additionally, since cookies expire after ninety days, most insights collected in these systems expire after that period.
For many companies, this is sufficient for segmenting purposes. However, if you’re looking for more tailored personalization, you may want to look further.
The preferred option would be using a CDP. This system will use a visitor’s PII (personally identifiable information) to collect and analyze multiple data points throughout the customer journey.
This means that interactions with a brand can be monitored across channels, thus, are not limited to the interactions with previous customers. Because it integrates data points from all sources, gaining a 360-view of customers is attainable.
CDPs use machine learning to sift through data to make segmentation efforts more straightforward to use across company departments.
The result of all these features is a comprehensive of your customers and website visitors in one place.
Naturally, one of the most critical elements of investing in new methods or technology is analyzing its impact.
There are several ways to do this, depending on your focus, monitor:
Investing in customer intelligence is on the rise and will soon be essential if you want to stay relevant to your target audience.
The jump to a customer intelligence mindset doesn’t have to be drastic, you can start with small steps such as mining your website’s behavioral data yourself. This will help you build up the evidence you need to make a business case.
As you come out of this point, be sure to keep the following in mind: