7 min read
In the modern world, the majority of businesses employ direct marketing practices to contact their prospects and promote their products or services. However, if you send direct mail to all of your prospects, or your customer service team, phone each lead you have, then your marketing activities can be incredibly expensive and inefficient. On top of this, if you continually bombard all of your prospects with information that isn’t relevant to their needs, then you’ll lose them as a potential lead.
Thankfully, customer modelling tools can help make your marketing activities much more efficient and cost-effective. This is because the process of modelling customer behaviour helps you identify which message, product, or service is the most appropriate for each customer in your database. While profiling and segmenting your audience can also help you with this process, customer modelling goes one step further. This is because it helps you predict how likely a prospect is to reply to a specific marketing message, or predict their long-term value to your business.
What is customer modelling?
Customer behaviour modelling is a form of predictive analysis. Using the data your business currently has available, models can be used to predict the future behaviour of your customers and prospects. Using the data that’s generated by the models, you can maximise the effectiveness of your marketing efforts and boost your ROI. This can be achieved by ensuring you’re only ever sending targeted, personalised, and highly relevant messaging.
However, although customer behaviour modelling is highly effective, building models can be an expensive and difficult task. This is because experienced analytics experts are expensive to employ, and the mathematical techniques they use are complex. As a result, the best way of running models is by using dedicated customer modelling tools. These can help model and score your customers, as well as perform other aspects of predictive analysis.
With this in mind, let’s take a look at the process of customer behaviour modelling in greater detail. We’ll start by taking a look at what customer modelling tools are, before analysing what they do and the benefits they provide to marketers. We’ll then conclude by looking at how Apteco’s customer modelling tools can help you make informed marketing decisions.
What are customer models?
Customer models are typically based on data your business has gathered from your current customers and prospects. Models are created using algorithms and they’re used to support a marketer’s decision-making process. These models can be applied in many different areas, such as determining whether customers will buy new products, or identifying which customers are most likely to lapse. The process of customer modelling works best when different models are calculated and compared to each other.
What can customer modelling be used for?
Customer behaviour modelling can be used for a wide variety of marketing purposes. For example, you can use models to:
- Predict the possibility of a new customer having a high lifetime value. If the model predicts this will be the case, then you can provide these customers with special preferences and serve them with highly-tailored marketing communications
- Provide you with a list of customers who are likely to lapse. Following this, you can then target these customers with personalised incentives that will stop them from churning
- Target direct marketing at customers who are most likely to take up or buy a product or service. This applies to both generating additional revenue from current customers and to identifying new prospects who are likely to respond in the desired way
In all of these situations, modelling is used to score a customer database. By scoring all customers in your database, you can identify the customers who should be included in your marketing activity, and any other groups of customers who have a high probability of converting.
Benefits of customer modelling tools
In order for your customer behaviour modelling to be effective, you need to employ the help of customer modelling tools. These can help ensure that your modelling is fast, accurate, and cost-effective.
When used correctly, customer modelling tools provide a number of benefits to marketers. Chiefly, predictive behaviour modelling can either help you select the best marketing actions to run for each of your customer groups, or it can be used to identify which of your customers are most likely to change their spending level. Using the customer behaviour insights generated by the models, you can make sure that each decision you make is backed by data and has the highest chance of success.
Plus, by employing what you’ve learnt from the modelling process, you can always ensure that you’re targeting specific customers with marketing actions that are tailored to suit them. Although you may generate an uptick in sales if you send all of your customers the same campaign, you may also lose customers if you’re continually sending them irrelevant information. By instead sending them targeted offers at opportune times, you will increase the effectiveness of your campaigns.
Similarly, another one of the main customer modelling benefits experienced by marketers is an improved ROI. Due to the fact customer modelling allows you to predict which of your customers will churn and which actions will cause them to remain long-term customers, the ROI of your cross-sell and retention campaigns will improve.
On top of this, when you effectively utilise the customer behaviour insights you’ve generated, you’ll create a better connection between your business and your customers. This is because your marketing activities will be better tailored towards their needs and your communications will be more relevant. As a result, your customers will not only enjoy the experience of shopping with your company, they’ll become loyal to your brand and may even provide you with word-of-mouth referrals.
Benefits to suit every objective
In addition to the benefits listed above, depending on the exact goals of your business, you can also experience lots of other customer modelling benefits. These include:
- Increasing response rates by targeting customers and prospects more effectively
- Creating a profile of your best customer and using this to acquire more customers that meet the profile
- Identifying markets with the most potential
- Finding your most responsive clients and targeting them with cross-sell and upsell opportunities
Apteco’s customer modelling tools
The customer modelling functionality in our tools has been designed to help you uncover patterns of behaviour in your data. This means all our tools can help you predict future customer behaviour and make informed marketing decisions that maximise your results. Using the help of our analytical tools, you can:
- Build profiles that identify the significant characteristics of a selection of your customers when compared with another set of records. By building profiles, you can improve your understanding of the characteristics of your current customers and analyse your strengths and weaknesses across market sectors. If required, you can even run profiling reports that highlight market sectors in which your business is over or under performing
- Perform a cluster analysis that will explore and identify natural groupings in a set of data points. You can then use these groups or clusters to better visualise your customer population and segment them for marketing purposes
- Use decision trees to define a selection of customers that you are interested in, and then to identify the characteristics these people share
- Run model reports to evaluate how well your model is identifying target groups
Apteco’s customer modelling tools can help you perform your analysis quickly and effectively. With the ability to process millions of records in just a few seconds, our customer modelling tools can create profile reports that highlight the characteristics that are statistically the most prevalent within your existing customer base. Using this information, you can then source more records that share these characteristics for lead generation and prospecting purposes.
In addition to this, our customer modelling tools also allow you to compare two groups of customers that have been acquired from different channels or have responded to different campaigns. This means that significant characteristics can be identified and utilised in future communications.
On top of this, our customer modelling tools can also streamline the process of creating and applying scoring models in order to select groups of customers for upcoming marketing campaigns. With our tools, there’s no need for you to create models on an external database and then apply your models into your original database. Due to this, you can greatly reduce the time and technical expertise required to produce accurate and insightful models. Plus, thanks to the integrated nature of the analysis, your marketing processes will become streamlined and more efficient.
What modelling techniques can I use?
Apteco’s customer modelling tools are highly advanced and they offer three main modelling techniques. These are:
Profiling: Using a patented Predictive Weight of Evidence (PWE) method that combines widely recognised Information Theory and Bayesian Probability, this technique scores individual customers and prospects. It’s fast, automatic, and requires a minimum of user input
Decision Tree Models (including CHAID): This method produces a set of rules that are ranked to identify distinct segments or groups that contain proportionally more of your best customers and prospects. Decision trees can also be applied to external databases for comparison purposes
Clustering: This form of modelling can be used to identify groups of customers and prospects with similar characteristics. It uses the K-Means technique to allocate each record to the nearest cluster centre, enabling you to better visualise and segment your database
On top of this, our customer modelling tools include a model report feature. This means that you can test any model using a holdout sample. Using this feature, you can easily and accurately identify the point at which your model produces the maximum return on investment (ROI) or keeps you within budget.