Source: What’s the difference between CRM, marketing automation and DMPs? | Econsultancy

To somebody like me who hasn’t worked at the sharp end of customer relationship management (CRM), it can be confusing to consider the theory.

I set out to discover where CRM, marketing automation, sales, and data management platforms cross paths, and how CRM is implemented.

CRM in layman’s terms

It is common for troubled CEOs to utter the immortal line, “we are putting the customer at the heart of everything we do”. Well, old-fashioned CRM did exactly that.

CRM programmes were designed to allow companies to foster customer feeling and loyalty, rather than simply transactional interactions. This focus on retention (keeping track of communication with the customer) delivered greater ROI than simply chasing more and more novel sales prospects.

CRM enables the analysis and management of customer interactions with sales, marketing and service departments, ultimately shaping the customer lifecycle but also, more broadly, organisational processes.

Isn’t that marketing automation?

Marketing automation systems often work closely with CRM software, indeed many CRM solutions have incorporated marketing automation functionality (e.g. Salesforce Pardot).

However automation is a fairly generic idea, reducing the repetitive labour of customer communications – for example, triggered emails or website messaging.

Characteristically, marketing automation has been used for lead nurturing, with resultant customers looked after by the CRM, but that distinction is perhaps no longer a helpful one, given marketing automation is more and more embedded with CRM systems.

How is CRM different from a data management platform?

Data management platforms (DMPs) are most associated with online advertising, where large amounts of cookie and campaign data can be managed (including third-party data), and are often managed entirely separately from CRM.

However, the integration of CRM and DMP platforms is a nascent but growing area. As Chris O’Hara points out, this can enable marketers to target non-openers of emails with display advertising (using anonymised email IDs), for example.

In Chris’s hypothetical example, a pizza company could deliver display ads during the week, up to Thursday (the day it knows certain customers are likely to order a pizza) when it could send an email coupon.

It makes sense that CRM and customer lifetime value data can be brought to bear on paid media, not just in an ad hoc fashion. It also makes sense that data management platforms should start to be used for more than simply display advertising, but to improve attribution of value to multiple marketing channels.

However, as many marketers make plain, increasing IT complexity can sometimes distract the organisation, particularly if there isn’t enough analyst capacity to dig into the newly expanded data.

Andrew Campbell, CRM expert, expands on this point:

“As the quantity of data increases, the need to identify quality data becomes a marketing imperative. Data management platforms have industrialised the processing and management of big data, but marketers need to find a way to drink from the hose!

“It is no longer practical (even in the cloud) to pull all available data (posts, tweets, app usage etc.) into a single Master Customer record.”

Where does CRM fit into small and large organisations?

CRM’s impact on sales, marketing and service makes it pretty central to any organisation. And CRM doesn’t just impact on these three departments, but should be viewed at the organisational level, often affecting supply chains and back-office processes.

Microsoft even uses the term XRM (‘anything’ relationship management) to define this idea of managing relationships across a business, not just the customer facing parts.

Customer data is often fragmented, stored in different parts of the organisation – bringing this together is one of the challenges of CRM. Some organisations have CRM departments that still sit separately to online marketing.

Using a slightly dry but useful typology model (see figure 1 below, taken from Econsultancy’s CRM in the Social Age report), we can look at the various development stages of CRM.

  1. Operational CRM: ‘reengineering the customer-facing business processes and systems to ensure the efficiency and accuracy of day-to-day operations across sales, marketing and customer service’.
  2. Analytical CRM: Storing, extracting, interpreting and reporting on customer data – to optimise business decisions and support customer-centricity.
  3. Collaborative CRM: ‘integration of the front- and back-office processes that combine to support customer interactions.’
  4. Social CRM: Deliver a consistent customer experience across social media, using analytics to support customer conversations and response handling. Integration of social data with broader CRM.

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