How to identify your ideal customer with CRM

Here’s a question for you – when you think of your ideal customer, what image pops into your head? Does one specific customer come to mind? Several different types of customers? Or, perhaps, nothing at all? When you sit down for business planning sessions it can sometimes feel like this question relies too much on guesswork and not data. Well, this is the blog for you!

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What do you need to consider with the data in your CRM?

We originally wrote a blog on this in 2011 (How to Implement CRM – Top Data Considerations) and figured it was about time to give it an update. So, one of the most, if not THE most significant factor when it comes to any CRM is the data stored in it. The basics of it are – the value of any CRM system is in the data contained within it.

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Visualising Data using Maximizer CRM

Well, this is quite the journey we have been on. This is the final article in a 3-part series that has looked at how Maximizer CRM helps you to firstly, Manage Data Integrity and then secondly, support that ‘clean data’ by feeding Repeatable & Scalable Processes. The final cog in the data machine is visualising the output data from the processes in a way that keeps the business moving in the right direction.

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Here’s why you need CRM for your B2B Marketing

Reading Time: 2mins In the past decade and going forward the best way for any company to stand out is with a brilliant B2B marketing strategy. That’s not to say that customer service, sales and leadership aren’t important. But with increasing global competition and the need to efficiently market a company’s brand, image, products, or services, more and more B2B organisations have started implementing marketing automation software.

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How to Manage Data Integrity using Maximizer CRM

Reading Time: 2min19s Effective and efficient CRM is not a pipedream, it is easily attainable when you understand what you need to get right on the platform so that the system can do the right things for you and the business. There are a number of elements that make up an effective and efficient CRM platform, one of which is data integrity. ‘Dirty’ data creates multiple headaches for the different departments in a business, from marketing to customer service, team members are left feeling embarrassed and frustrated.

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CRM and Artificial Intelligence (AI)

I’m involved with two projects at the moment that are wildly different. But they have something in common. They are both using CRM to deliver Artificial Intelligence (AI) into business processes. Most importantly, they are using CRM to deliver AI into business processes at very low cost. And that’s the point of this article.

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Client profiling for profit within professional services firms

Just how well do you know your clients? Not just the standard stuff required to comply with Know Your Client (KYC) or Anti Money Laundering (AML) legislation. Could you describe your clients? Could you describe them in terms that might help you to find more clients? The answers to these questions lie at the heart of client profiling. The ability to describe an “ideal client” is at the heart of marketing best practice.

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A decade of CRM – A look at how CRM has changed over the last 10 years

Nostalgia isn’t what it used to be! The beginning of a new decade feels like the right time for a look back at what has happened to CRM in the teenies. Like any teenager, this was never going to be an easy period of development. The preceding decade has seen the birth of modern CRM systems. The parents (contact management and sales force automation) were proud of the youngster. But then came the tricky teenage years. The awkward times when things change. So what were the highs, and the lows of the journey to maturity?

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What is the best strategy for Data Migration?

New Year, new CRM system? For many organisations considering changing CRM platform, data migration is a major worry. How much, and what sort of data should you move? What is the process for moving data, and how do you ensure that the new CRM system doesn’t start life with the same messy data as the old one?

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