5 easy steps to set up Predictive customer retention

customer retention

You’ve read all the success stories about how firms have used AI to interrogate their customer data to increase customer retention.

They implement a clever automated solution that saves them from the brink of oblivion and catapults them to the forefront of their industry.

Yay!

These success stories are becoming more and more commonplace and seem to be happening in pretty much any and every industry you can think of.

So, on reflection, it makes sense that you see an opportunity to use AI and leverage your own data to increase customer retention or boost profit margins.

But how?

Don’t believe the hype!

Well, in this case you should.

Many of these stories are true and for each story you read there would be 5 to 10 success stories that aren’t being lauded as a case study to trump all case studies.

AI is becoming widespread in every industry and, most importantly, it’s having a significant impact on the bottom line of these companies.

We are seeing an emerging trend in so many industries where firms who have implemented AI are growing and expanding, whilst their non-AI counterparts are lagging further and further behind.

So is it time to jump on the band wagon?

Errr, yep!

You would have already decided that it’s worth investigating what AI can do to increase customer retention.  The barrier might be that it’s not that straight forward a task to get started. 

It’s true, you can’t download and AI app that will solve your problem.

But that won’t stop you from embarking on an AI project. 

One that uses your customer and organisation data to allow you and your team to more efficiently and effectively market to your existing and new customers.

Start small and grow from there

An early stage Proof of Concept is a quick (and economical) way to implement a small project to test if your objectives can be achieved.

This PoC should take 2-3 months and should focus on a sub-group of your customers or a particular product/product range. 

The stages of the PoC should be:

 

  1. Analyse your historical data
  2. Develop and test the machine learning algorithms to achieve the objectives (we can help here)
  3. Create the automation processes
  4. Integrate the above with your existing CRM and mailing system
  5. Monitor and review the impact of PoC

 

It’s important to outline a strategic road map or action plan for the project. 

It’s critical to get buy in from the C-Suite too.

From small acorns, oak trees grow

The results of the PoC will be evident way before the end of the 3 months. 

You’ll be able to gauge the potential of the project within the first month.

You should be able to fine tune and further improve this result in the final months.

Communicate progress and results (good or bad) with everyone and start planning the next phase before the end of this PoC.  

If the PoC is a success, you’ll be keen to extend it beyond the initial subset of data. That may require support from others so make sure you create your own success story and shout it from the rooftops.  

Good luck and don’t look down!

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