Data segmentation and enrichment for email marketing in 3 steps

By 17 August 2021No Comments

Measurement is knowledge and data segmentation and profiling helps you. Ultimately, you want to use your email marketing data to get a good picture of who your customer is. This will help you to have the best 1-to-1 dialogue. It will enable you to achieve your end goal: increasing conversion, generating commitment/loyalty and/or saving time.

You cannot achieve this with email marketing without applying data segmentation and profile enrichment. In this article, we will explain which three steps organisations generally take in the process of data enrichment and segmentation, and why each step involves a constant interplay with the other 2 steps. We will also give a number of concrete examples.

Data segmentation

This series of articles about data consists of 4 parts. In this article we will address the highlighted part of this model. We will talk about segmentation, data enrichment and personalisation. In the other articles you will be able to read about the other parts of the model.

1) Data segmentation for email marketing

Email segmentation and data enrichment are integrally connected, and involve a constant interplay. With segmentation you split up your email marketing into various groups in order to send content that is as relevant as possible, based on (enriched) data. This will help you realise, for example, higher open rates, greater relevancy and better deliverability.

Step 1 is basic segmentation using the information that you request for a registration for a newsletter, event or download. The information that you need from your customer varies according to sector and the purpose you collect the contact details for. If you operate a webshop, gender is more important than if you were to run an agency, for example. And if you work in the B2B sector you would probably find it more important to know the size of the company and the position of your contact within it.

With your basic segmentation as a starting point, you proceed to enrich your data for further segmentation.

Below we will also give some examples of segmentation of email lists:

  • Geographic data: country, city, population density, language, climate
  • Demographic data: age, gender, income, profession, marital status
  • Psychographic data: lifestyle, activities, personality
  • Behavioural data: previous purchases, browsing behaviour on the website, involvement

In addition to target group segmentation, increasingly more organisations are moving towards content segmentation.

2) After (basic) data segmentation: data enrichment

Step 2 involves the enrichment of your data, so that you can also segment on the basis of, for example, psychographic data or behavioural data. A customer goes through various phases. In most cases you get the best results from enriching your contacts’ data within the first 30 days of registration/subscribing.

In that period, your contact is also in the interest and consideration phase. We also refer to this period as the 30-day honeymoon period, because a person’s engagement and willingness to share data is high.

Some data will need to be enriched explicitly, whilst other data can be enriched automatically. This is why we make the distinction between the ‘automatic’ and ‘non-automatic’ enrichment of data.

Data that you cannot enrich automatically

It is not possible to enrich data such as age, gender, address, etc. automatically (just look at someone’s click behaviour and try to guess their age;)). And so you can find this out by asking the customer explicitly for this information. You can do this in the following ways:

Landing page with form: for the non-automatic enrichment of data you usually use a landing page with a (pre-filled) form. On this form you ask for various details regarding for example an event, newsletter subscription, registration for a promotion or change of preferences. You can, for example, indicate as standard in every email that customers “may” change their preferences themselves in order to receive more customised communication, or link a particular promotion to it that is of interest to them. This will help to make more customers willing to give their details.

Gamification: you can apply the principle of gamification on a landing page. Put together a quiz, let customers spin a ‘wheel of fortune’, have them do a puzzle or some other game. The answers that your contacts give during or after the game are a smart way of enriching their profile. Many large organisations such as the Utrecht Jaarbeurs and Sunny Cars already use the principle of gamification.

Some data will need to be enriched explicitly, whilst other data can be enriched automatically. This is why I make the distinction between the ‘automatic’ and ‘non-automatic’ enrichment of data.

Data that you enrich automatically: lead scoring

A principle that many organisations apply is the automatic enrichment of data by means of lead scoring. This often involves the implicit measurement of properties through a person’s online behaviour. This online behaviour that you measure is also referred to as engagement.

How does this work in practice? With lead scoring, you award points to certain actions in an email or through other marketing channels, like your website. An “open” may be worth 10 points, a click in an email 20 points, reading your blog articles or your product pages online 5 points per page and a visit to an event 50 points.

A database field is automatically given a numerical value, which determines which phase a person currently is in (awareness, consideration or decision). With a certain number of points you can see that someone is, for example, ready to buy (sales ready) and so you can send them an offer.

Below are a few examples of how you can use lead scoring:

  • Lead scoring in a lead nurturing flow: send a flow in which you inform your contacts about your professional field, service and/or product. In this flow you award points for clicks and opens. This helps you find out the preferences of the recipient and you can divide these contacts into categories such as ‘sales ready’, interest in city trips or sun holidays
  • Measure website behaviour through web lead scoring: award points to someone’s browsing behaviour on the website. For example, you can do this for every email (campaign) that you send. You then send an automatic follow-up at the right moment or inform your sales colleague that the sales qualified lead is ready for a phone call

3) Personalise communication

Based on explicitly requested data and automatically collected data, you personalise your content in campaigns and communication. You then send messages via various channels, including email. Step 3 is therefore a constant interplay with step 1 and step 2.

Are you getting started on the basis of data? If so, you will come across the term data-driven marketing. Data-driven email marketing is generally a part of a data-driven marketing approach.

Tripolis also has extensive possibilities for integrating data, segmentation and personalisation. This is automated and can to a (very) large extent be modified to the customer and the phase they are in.

If you want to personalise content on a large scale, and do this on the basis of sources other than email, then you also need a central place where you can collect your data. This would usually be a data warehouse, DMP or CDP. We will therefore tell you more about this in the final article in this series.

How can we help you further with data?

Should you have any further questions or wish to brainstorm about your data puzzle, our advisers are here for you. We regard marketing automation as a strategic game, and will be happy to help you get on with data so that you can optimally use the benefits in your customer journey.