Lindar Media in the press!

July 27th, 2017 by Sam

Lindar Media is starting to make headlines, and for good reasons!

Our Acquisition Operations Manager (formerly Head of SEO) Phil Blackwell wrote an article for iGB Affiliate magazine on bingo affiliates, and why they rank so badly on Google.

It’s an interesting read (if we do say so ourselves), and all the data used in the article was sourced in house by Phil. It was a real labour of love, but it’s nice to see Lindar Media getting international attention!

If you want to take a read for yourself, the article can be found in iGB’s June/July issue, and can also be viewed online through iGB’s digital magazine reader.

Best of all, this is only the start. Keep an eye out for more magazine coverage in future…

Data-Driven Marketing: How to use customer data to increase profits

December 5th, 2016 by Sam

Trying to get your head around CRM can be a little tricky. Good thing there are some excellent resources helping me along the way. The book “Drilling Down: Turning customer data into profits with a spreadsheet” by Jim Novo has helped me to grasp hold of the fundamental ideas of CRM. Here’s a little of what I learnt.

The definition of a customer, as defined by Jim Novo in his book “Drilling Down: Turning customer data into profits with a spreadsheet” is “someone who:

  1. Has Purchased from you in the past, and
  2. Is expected to purchase in the future”

Although this definition doesn’t seem particularly ground-breaking, it brings attention to the fact that just because someone was at one stage a customer, it doesn’t mean they can necessarily still be described as such.

Jim Novo continues to break down this definition by describing two types of customer profiles.

Firstly, we have customer demographics. This describes attributes such as age, gender, location and hobbies, which can be very informative for deciding on content for websites and advertisements. Some customers might love everything pink, sparkly and fluffy… others however may be less appreciative of this style of content. This information however is limited – how can we really know if a customer is going to continue being a customer, and what the future relationship with them will be like?

The answer is behaviour – past and current behaviour is the way we can predict future behaviour.


There are a few other fundamental ideas which must be understood in order to succeed. Customers want to win at what Jim Novo describes as the ‘customer game’. Communication programmes that allow customers to feel in control are essential for this.

These continuous communication programmes allow an Action-Reaction-Feedback-Repeat cycle to form. An action is taken in the form of a promotion or offer and the customer will react to this engagement attempt providing feedback. This feedback can be analysed to inform future promotions– did the customer respond in a way you were expecting?

So when is the best time to take action?

Firstly, we need to document what constitutes normal customer behaviour. How often does a customer normally visit your website, or buy a product? How much would they typically spend? When a customer diverges from this normal behaviour, something has changed. This can be good or bad. Either way, it’s time to take action.

Predicting the future with RFM

But how do we identify high value customers, those who are most likely to respond to an action? How do we predict the future?

The answer to this is RFM (Recency, Frequency and Monetary). Customers who have deposited recently are more likely to deposit again compared with customers who have not deposited in a while. Customers who frequently deposit are more likely to deposit again compared with customers who don’t deposit as frequently. Similarly, customers who spend more money are likely to spend more money in the future. Scoring customers from high to low on these three measures provide an indication of who is most likely to respond – we place these customers at the top of the scale.

One of the most remarkable things about this scale is the ability to detect change. Customers can move up and down the scale, representing their change in value as a customer.

Change is important. If a customer climbs up the scale you need to encourage them to continue doing so. If a customer drops down however, you need to take drastic action to win them back. As you can see, RFM is an incredibly powerful and dynamic tool. It provides in-depth and informative data that helps to drive your business forward. How would you use influential data of RFM to skyrocket your business?


Novo, J. (2004). Drilling down: Turning customer data into profits with a spreadsheet, Inc.,.

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