When most people think of Customer Intelligence, they think of the collection and analysis of data, specifically where the data collected allows brands to better understand their customer; what they need, when and where they’re interacting with the brand, and why. On the basis of this information, brands can adapt to the demands of their customer base to make them feel more understood and valued as individuals. We can analyse behaviour against any e-commerce platform, online game, app, or social network by collecting data at different points of contact with the customer during their Customer Journey, across different channels, via different devices.
We can source data from a huge variety of different places including websites, CRM systems, Marketing Automation systems, social media, and more.
Each source provides a different set of data which, traditionally, would be isolated and analysed on its own. For example, a new customer creates an account on a website and makes a purchase; how did they get to this point? How long did they browse pre-purchase? Have they been exposed to any advertising? How many different products did they look at before making their decision? Our aim is to centralise all this information in a Data Lake that allows us to connect and integrate different data points in order to generate a more unified vision of the entire customer experience. This way, it’s possible to determine which customers have created an account, browsed the site and, finally, purchased through your app. Without integrated information, we would have to study their behaviour on the website and their behaviour on the app as if it were the behaviours of two different people.
Your behaviour analytics strategy
To monitor behaviour, we need to define and record every event – and in this case, an event refers to an action carried out by the customer which involves interacting with a product or service offered by our brand.
A strategy focused on Behavioural Analytics should include the following six steps:
Step 1: Define your business objectives and analytics
As with any project focused on analysis, your first step should be to identify your business objectives and establish which KPIs will be useful in achieving those objectives. For example, if your objective is to improve customer loyalty suggested KPIs would include:
- The Customer Profitability Score (CPS) which measures the profitability of an individual customer over a specific period of time
- The Lifetime Value (LTV) which measure the value of a customer in regards to their relationship with the brand over time and helps us to optimise acquisition costs
- The Net Promoter Score (NPS) which measures customer loyalty
- The Churn Rate which helps brands to understand the rate of abandonment and reason behind instances of abandonment.
Step 2: Determine the customer journey
At this point, it’s a question of figuring out what actions are being carried out by your customers at what points along their journey, in order to determine which events will be used to analyse their behaviour. Sticking with our last example, if we were to establish a customer loyalty programme, the customer journey might look something like this:
- Action (making a purchase, inviting friends and family, etc.)
- Redemption of incentive
- Accessing the loyalty programme URL
- Registering on the website, sharing personal data
- Downloading the app
- Opening the app
- Accumulation of points
- Applying for incentives
- Redeeming/spending incentives
Step 3: Identifying customers
Deciding on the best way to identify individual customers (e.g. email, telephone, unique customer identifiers, fingerprints, etc.) is essential. You have to decide this before beginning to record events coming through from different sources in order to ensure each customer is traceable no matter what channel they’re on or what device they’re using. You’ll also need to determine how each customer will be treated and identified before settling on a customer identifier. An understanding of the customer is the key to optimising acquisition and growth efforts.
Step 4: Define your data capture strategy
After you’ve mapped your customer’s journey and chosen which KPIs to monitor, the next step is to identify which events need to be taken into consideration when analysing behaviour across channels. You’ll need to develop your data capture strategy:
- Data to be collected at each event
- Methods and means of data collection
- Most suitable moments for capture
- Necessary resources
- Data sources and the channels from which they originate
- Storage of information by channel
- Data integration
Also, you might want to define the different attributes that will help to characterise your customers (socio-demographic variables, preferences, interests, etc.) against their behaviour (type of action, time to complete, relationship with other events) in order to understand how the customer journey varies according to buyer type, channel, or device.
Step 5: Record the events
With your strategy defined we move on to the recording stage. The first step is to send everything you’ve recorded to the Data Lake and then determine if you have all the necessary elements to trace the customer journey, study the behaviour of the individual and measure and report back on all defined KPIs.
Step 6: Analyse customer behaviour
Finally, it’s time to study the data available in order to deepen your understanding of the customer. Ask yourself:
- When buying a product or service, what are your customer conversion routes?
- How many interactions/changes between channel and device have taken place up to that point?
- How often do customers convert?
- What is the relationship between the number of purchases made and the time spent on your website before the conversion took place?
- Which customers are more likely to make a purchase?
- When are customers getting stuck during the purchasing or onboarding process? Are customers asking for your help?
- How can you keep their attention during the searching/browsing phase of their customer journey?
- Do all your channels work in the same way or is progress made at different stages of the conversion funnel dependent on the channel itself?
- On average, how long does it take for customers to move from one stage of the journey to another? How long does it take them to move between the different points of contact?
- How do customers react to changes in the process, or to the product or service itself?
- What additional services are needed in order to encourage conversion?
- What actions take place immediately before a customer withdraws from the purchasing process?
- Which retention strategies work best?
- Which customers are more likely to stay loyal?
Once you have the answers to these questions, it’ll be easier to rethink and redefine how you communicate with your customers, how you attract and retain them, how you increase brand loyalty and exceed their expectations.
The benefits of this approach
By following these six steps you can develop a strategy that will help you to improve capture, activation, conversion, retention and sales rates through custom messaging and personalised experiences based on your analysis. You can increase the effectiveness of your campaigns and, subsequently, optimise your ROI. Your ability to promote cross-selling and up-sell actions will increase, as will customer lifetime value. A better understanding of your customer means new and improved products and services, as well as a happier and more engaged customer base. In the end, an understanding of the customer is the key to a more human-centred organisation, and a more human-centred organisation means more value for shareholders and society as a whole.