3 Examples of how to Use Intelligent Filtering

On: Sep 3, 2014    In: Intelligence, Tips & Best Practices

We know why our Intelligent Services can be beneficial for your business, but we also know why it can be quite complicated and that sometimes examples are the best way to explain it. In this post we will illustrate some of the ways you can use Intelligent Filtering to:

  • Reduce costs
  • Increase ROI
  • Improve customer experience

cupid_(2)No longer waste money on sending text messages to unreachable recipients

The data coming from our phone number intelligence database shows us that a large percentage (around 12%, reduced from 20% last year) of the messages sent via SMS are sent to numbers that no longer exist.

This means that around 20% of the messages our customers were sending, were a complete waste of money. By turning on what is commonly called “The Dead Filter” those customers can easily send less messages and reduce costs by no longer sending to those numbers without changing anything at all about their campaigns.

There is no need for additional cost, reporting, analysis or effort, they can just continue to send the same messages to their contacts in the knowledge that the Dynmark platform will automatically remove any messages being sent to numbers that are not associated with a mobile network.

Intelligent-Filtering-AnswerDon’t send messages to customers who won’t appreciate it

All forms of customer communication can run into problems when customers find them intrusive or annoying. This isn’t always the fault of the brand and can simply be down to the fact that some people don’t appreciate mobile messaging (find out more about customer profiles).

In order to avoid the kind of brand damage that can be caused by these sorts of customers, it can be a good idea to prevent from sending to them in the first place. Traditionally, there would have to have been significant analysis of all messaging campaigns sent to a recipient to identify which would cause offence, and whether that user would opt out, or respond with expletives.

Using the phone number intelligence database, we are able to take the work out of that for you, by analysing billions of messages sent to over 70 million numbers, we are able to predict which are more like to be receptive to mobile messaging and which won’t. This means our customers can simply switch on their filtering and carry on with their campaigns, reassured that the numbers most likely to respond badly to their campaigns are removed.

We can even do this per vertical, so if you are sending a retail message, you can avoid sending messages to those numbers that are more likely to opt out of retail messages.

Send messages only to relevant segments of people

Depending on what type of message you are planning on sending, not all of your audience will need or want to receive it.

For example, if you are sending a message relating to travel offers, it might be relevant to send it to people who travel a lot.

Or if it’s a message about your iOS app, why send it to people who aren’t using iOS devices? Filter them out.

Send campaigns that require an inbound response to people who are more likely to respond.

There are of course many ways you can use Intelligent Filtering and these are just a few examples, but hopefully this gives you an idea of what can be gained and how easy it is to implement.

Big Data; Profiling Your Customers