The field of data management is rife with acronyms for solutions that can seem vague like Customer Data Platform (CDP), Data Management Platform (DMP) and, in our case, Master Data Management (MDM). This is not exactly what I imagined I would be obsessing about as a marketer at this point in my career.

But think about this:

  • By 2020, 51 per cent of consumers expect that companies will anticipate their needs and make relevant suggestions before they make contact. (Source)
  • 78 per cent of US Internet users said personally relevant content from brands increases their purchase intent. (Source)
  • Personalisation reduces acquisition costs as much as 50 per cent, lifts revenues by 5-15 per cent, and increases the efficiency of marketing spend by 10-30 per cent. (Source)

Delivering increasingly personalised and valuable content, tools, and offers to customers and sales agents (e.g. independent insurance agents, financial advisers, physicians) helps marketing become the measurable growth and revenue engine it is intended to be.

And it all starts with data and a data operating model that ensures the value of the data and how you can use it grows over time. That’s managing data for marketing and customer experience and that’s not so boring after all.

Prospect to Customer Data for Marketing and Experience

From the time a lead is identified (i.e. marketing qualified lead, MQL) through a renewal on a multi-year, loyal customer, we have the opportunity to use data to manage how we attract and engage via:

  • Segmentation and targeting of ideal customer types or accounts (e.g. account based marketing or ABM)
  • Identifying new leads that look like your best customers (e.g. look-a-likes)
  • Behavioural tracking and insight (e.g. paying attention to what people do and where their interests lie)
  • Preference management (i.e. what are people’s stated interests and preferred channels)
  • Predictive marketing and service offerings (e.g. combine new data sources to reveal predictable behaviours; a person who buys and installs smart home technology for security and safety benefits is likely a better insurance risk as they are more inclined to maintain their home and anticipate problems before they ever become claims.)
  • Individualised marketing by delivering personalised content, tools and offers to individuals that increases the value they feel from the brand and drives them to valuable actions (e.g. delivering content relevant to where and how they live)

While there is a natural break-point between pre- and post-acquisition, strategically it makes sense to think about the entire customer journey from unknown lead to loyal customer. If your business model includes a sales agent of some sort like a financial advisor in wealth management, then that agent has their own journey. They deserve the same increasingly personalized engagement now made a bit more complex as you now need to associate them with an individual prospect and customer.

DMPs vs. CDPs vs CRMs

Acquiring, using, updating “cleaning” and growing customer data for marketing requires a creative mind and an intensely detailed obsessive mind. The creative part is about imagining what is possible. Very few brands are delivering seamless and intuitive personalised marketing. Even Amazon, the archetype for all things good and data-focused still promotes gift product ideas to me based upon a one-time gift purchase for cousin Bob. Imagining what could be possible – delivering personalised recommendation based upon the house and property you own and the trending weather in your neighbourhood and the search intent of your neighbours, for example – takes creative vision.

Detailing all of the data fields necessary to make that possible and then map out how to source and maintain that data takes the marketing equivalent of an obsessive compulsive (dis)order.

Data Management Platforms or DMPs were defined by advertisers, publishers and the tech companies who support them – like Adobe. Here’s how Kiki Burton defines DMP on the Adobe Blog:

“A DMP, or data management platform, is a tool used to consolidate the disperse data sets of a company across first, second, third-party channels. It manages the segmentation and identity definition of user to then provide cohesive audience targeting across all of the various channels where you might be engaging with a consumer.

Forrester Research defined a DMP as “a unified technology platform that intakes disparate first-, second-, and third-party datasets, provides normalisation and segmentation on that data, and allows a user to push the resulting segmentation into live interactive channel environments.”

In other words, it pulls data from a bunch of different, potentially unrelated sources and allows organisations to define specific audience segments to which they can provide distinct marketing experiences.”

Many consultants sum up DMPs as useful for acquisition marketing – finding and attracting your next customers.

Customer Data Platforms or CDPs are newer. They stress the first party data part of the first, second, third-party data layer cake. Some definitions focus on known customers while many extend from prospect to customer. Tealium (channeling the CDP Institute) describes it this way:

“The CDP Institute defines a Customer Data Platform as “a marketer-managed system that creates a persistent, unified customer database that is accessible to other systems.” Basically it’s a system that centralises customer data from all sources, unifies this data into customer profiles and then makes this data available to other systems for marketing campaigns, customer service and all customer experience initiatives.”

Digiday tries to sum up the difference between CDPs and DMPs:

“CDPs mainly analyse first-party data based on real consumer identities, while DMPs largely examine consolidated third-party data based on cookies. A good way to think about the difference is CDPs can be used to nurture the relationship with existing consumers, while DMPs are mainly used to acquire lookalike audiences.”

Some people describe CDPs as the CRM for the B2C set. It’s not clear whether the rise of CDP is due more to what attracts venture capital (money in search of a problem and solution) or a true unmet need at the enterprise level.

Customer Relationship Management systems or CRMs have been around since the eighties and nineties (the acronym, CRM, is traced to 1995.) They are most often described either as the sales team’s answer for customer and prospect sales management or the company’s for delivering service and value to existing customers.

The Salesforce definition of CRM goes like this:

“Customer relationship management (CRM) is a technology for managing all your company’s relationships and interactions with customers and potential customers. The goal is simple: Improve business relationships. A CRM system helps companies stay connected to customers, streamline processes, and improve profitability.

When people talk about CRM, they are usually referring to a CRM system, a tool that helps with contact management, sales management, productivity, and more.

A CRM solution helps you focus on your organisation’s relationships with individual people — including customers, service users, colleagues, or suppliers — throughout your lifecycle with them, including finding new customers, winning their business, and providing support and additional services throughout the relationship.”

What is Your Data Solution?

There is a lot of overlap in the definitions of these systems. Each industry and each brand is different enough that there is no one right answer. Unfortunately, it leaves the brand marketer with the chore of defining their own need and then labeling it – whatever the hell you want.

  • Companies with strong sales practices, teams and culture may want to build on a CRM-based model with some additional system for acquisition marketing
  • B2C companies who rely on attracting a steady flow of customers and need to scale via look-a-like marketing via ad networks and publishers may want to lean into DMPs
  • Companies who may sell via a few channels including bridging B2C and B2B marketing or who might be behind in marketing automation may want to define a CDP-like solution that serves both acquisition and customer marketing.

Here are some suggestions to help the non-data geek marketer consider the right options (you can also check out CDP-provider NGData and their comparison of CDPs vs. DMPs and Digiday’s comparison of all three):

  • Create a vision for how you want to attract and engage new customers and how you want to serve those you already have. How “individualised” will you go? How important will Account Based Marketing (ABM) be to acquiring new customers?
  • Understand how you can create a continuous path for unknowns to paying customers. Can you practically hope to build a single data resource or do you need to separate acquisition efforts from customer experience?
  • Define your commitment to finding new ways to combine 1st, 2nd, and 3rd party data to improve the efficiency of potentially both acquisition and customer marketing. If you want to aggressively experiment and “own” the lessons learned and outcomes then it may point you to a Cloud-based, owned solution.
  • Clarify the vision and commitment for integrating sales and marketing. If your future depends on it, then start putting the data infrastructure in place now. It may take years to get it right.

Welcome to the next age of data-drive marketing. Let’s learn from each other.

About the author

This post was originally published on The Digital Influence Mapping Project and is reprinted with permission of the author, John Hall, VP Enterprise Digital Marketing for data-driven, integrated marketing at Travelers.

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