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Exploring the Crucial Role of Data in CRM: An interview with Conor Doyle, Head of Sales at DQ Global

Workbooks recently sat down for a chat with Conor Doyle, Head of Sales at our valued long-time partner DQ Global to discuss the growing importance of data quality in CRM systems, how it drives business success and prepares for the future as well as it’s impact on AI.   

As our customers and clients know, at Workbooks we never stop thinking about how CRM systems and processes can be refined, evolved and optimised – and ensuring pristine data quality is a totally crucial part of doing that. Any CRM system, after all, is only ever as good as the data that’s fed into it.  

And nobody knows data quality like DQ: it’s right there in the name, and the list of clients they’ve helped – including major internationals such as 3M, Mandarin Oriental Hotel Group, Savills and Bloomsbury Publishing – speaks for itself. So who better to help us explore some of the questions and issues currently circulating around the topic of data quality in CRM?    

[Workbooks] At Workbooks we’re always trying to give customers and prospective customers a full, holistic picture of what our offering looks like, and data quality is essential to that – yet also tricky because it’s so foundational. For example, we have CPQ, we have Spotler, we’ve got marketing automation, which are all important parts of what we do, what you might call vertical layers with clear benefits. Data quality is more of a horizontal layer in that it underlies absolutely everything, yet as such paradoxically maybe its importance isn’t always obvious. So my first question really, Conor, is can you help readers understand why organisations need to care about data quality?  

[Conor Doyle] You’re right that it’s not immediately obvious, and I think the problem is that it can be hard to quantify the value of specific data quality optimisation measures. For instance, I was recently describing all the tech layers that businesses have in place – we’ve  got marketing automation, we’ve got a CRM system, we’ve got a quoting system and so on – and it’s obvious why we have them: we want to sell more, we want to waste less, we want to remove risk, we want to drive business value. But when it comes to specific data quality measures maybe the benefit isn’t immediately apparent. Yet in fact the benefits are huge! Take merging, for instance integrating records for an ‘Andy’ and an ‘Andrew’ who are in fact the same customer. Do that merge and you’ve got an entire buying history you can run analytics on, and as a result you can drive real business value, emailing the customer at the right time, getting more business out of them, simply building a better rapport with them. Merging may seem mundane or boring, yet in fact no part of the organisation works as well as it should if those two records aren’t merged.  

[WB] And at a certain point you need a CRM system for that, right? Otherwise it becomes totally unmanageable and has unexpected impacts elsewhere?  

[CD] Here’s a recent example of exactly that. We had a client with something like 5 million records in their database and wanted to remove duplicates. But that meant that suddenly the support desk, who had been receiving say 100 merge requests per month, were all of a sudden getting hit with six times that. As a result the organisation was looking at hiring a load of people to deal with the increase, but luckily we were able to say to them, ‘Look, let’s implement a tech solution that will automatically merge hundreds of thousands of records and get the support desk workload back down to where it was’ – and it’s now actually lower than previously! 

[WB] Can you maybe talk a little about the importance of data quality specifically in the present moment?  

[CD] Sure. So you’ve started to drive business value through improved data quality – that’s what we’re always trying to do for our clients. But go a layer up, take a little bit more dramatic of a bird’s-eye-view, and what we’re really trying to do is prepare them for AI and machine learning, which we know is a massive wave that’s coming. And AI and machine learning are literally all about data quality, since an AI is in a sense nothing more than the sum of the data it’s learned from. Good quality data is the foundation of an organisation’s future success in the coming world of AI – and of any number of other developments we’re not even thinking about yet.  

[WB] So what we need to help people understand is that data quality is not only going to provide business value today – though it’s definitely going to do that – but it’s also going to be the foundation for future success in a world that’s soon going to look radically different?  

[CD] Exactly.  

[WB] Moving away from the future for a moment, I’d love to hear your thoughts on the ‘how’ of getting organisations and their people more invested in data quality in CRM systems.  

[CD] Well, it might sound obvious, but it bears stating anyway: a CRM system is there to do a job, it’s there to serve the business and the people from top to bottom that make the business run. We talk about a triangle of people, processes and technology, which is absolutely right, but we have to remember that if the people start to feel like they’re being governed and dictated-to by the processes and the tech then … well, people hate that, they hate to feel arbitrarily governed, so they’re going to back out and not be fully invested. So it’s totally key to create a data-driven culture where the three sides of the triangle are all fully coordinated and balanced, where there’s the transparency that’s needed to get real buy-in from the team. That’s going to create value today, and it’s really essential for laying the data foundations for future success, too.  

[WB] Yeah, adoption is key – it might as well be written above the entrance to Workbooks! Without it the absolute best CRM system isn’t really any more use than any other.  

[CD] Totally. What might be less obvious, though, is that actually adoption has a big role to play in data quality itself, because one of the best ways of maintaining quality is for people to be actually using the system. If they aren’t invested, if they don’t trust it, then maybe they’re doing their real day-to-day work out of Excel spreadsheets they do feel they can trust – which means the CRM system doesn’t reflect that up-to-date reality, and in fact is no longer trustworthy. It’s a self-fulfilling prophecy or a vicious cycle or whatever, and there’s a similar thing with analytics. I don’t have the exact figures to hand right now, but an astonishing number of management teams and C-Suite folk simply don’t trust the data available to them, and therefore the analytics based on that data, and as a result aren’t using it to drive their decision-making.  

[WB] That’s a big problem.  

[CD] You can see how big it is when you look at what happens when they do use the data. I was talking with a client only the other day who did an audit and found that they literally had more business applications of various kinds in play than had individual employees, all operating in this siloed way that didn’t join up. And when they joined those applications up they were able to get a global, integrated picture of who they were doing business with – and increased their cross-sells revenue by 30%, give or take.  

[WB] 30% is huge, isn’t it?! 

[CD] Beyond huge. As you know, businesses expend vast amounts of energy to achieve growth on the order of 2% or 3%. And this was a reasonably minor tech shift that achieved something like 10 or 15 times that, and they’ve now got 700% ROI on their marketing spend. And there are literally hundreds of examples. Let’s say you’re dealing with a huge multinational like JPMorgan. Well, you’re actually dealing with maybe dozens of separate branches of that organisation as separate accounts, accounts with their own sets of data. But if you’ve got properly bedded-in and fully adopted data-management systems in place you can join them all up into a single picture, and that allows you to drive revenue by taking advantage of that scale, say by offering discounted rates or whatever based on the organisation’s overall spend. This is the kind of thing we should be talking about when we’re explaining the importance of data quality!  

[WB] That seems like a good, inspirational note to end on! I feel like we’ve barely scratched the surface of what we could talk about, but I know you’re busy and don’t want to eat into your day too much … 

[CD] We’ll talk again about this I’m sure. None of these issues and opportunities are going anywhere!  

If you are having issues with the data quality within your CRM system, or are looking to switch CRM providers, contact us today and lets work together to see how we can help your CRM reach its full potential