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Succeeding with Data-Driven Marketing Starts with Your Data
But you may not be using it to your advantage
As you pursue a data-driven marketing strategy, you are making certain assumptions. Firstly, you recognize that your prospective consumers have changed how they make purchasing decisions and how they consume media and receive social messages. The old funnel metaphor has been replaced by a series of interlocking spirals. Brand is still important, but only one factor.
Secondly, you understand your prospects and your current customers interact with your brand through multiple channels at different times in a very fragmented journey to get to the decision to engage with you.
This fragmented journey and multi-channeled interaction with your brand has resulted in a hodgepodge of customer and prospect data sets. Although you may be awash in data from your CRM database, website, AdWords analytics, and email campaign statistics – you may still not be able to answer key questions such as:
- Who is consuming the media that we produce?
- Which ads are doing well on what media channels?
- What is influencing the consumer's purchase decisions?
- What are consumers buying and where are they buying from?
And, when a prospect becomes a customer, what do we know about them? We may have a great deal of data but not have a clear understanding of our customer's digital behavior, buying preferences, or all the other "digital signals" they have provided.
Connecting the "data dots" from prospect to lead to customer to loyalty requires a new approach to data collection, aggregation across channels, and utilization.
The Solution is Hyper-Personalization Through Data Clarity
Understand and interact with your targeted segments at the individual level through an integrated data view
Step One Creating the consolidated customer view
You may already have many of the components of this consolidated view from your CRM and other data-oriented tools. But this data resides in discrete silos across your enterprise. The CDP takes the data you already have, combines it to create a meaningful customer profile, and makes it accessible across your organization, from marketing to sales to call center to customer service.
The process starts by combining as much data as possible into the CDP and developing an automated process for adding to it over time. Creating models that group customer profiles that behave in similar ways requires advanced analytics of a best-of-breed CDP to process the data and utilize machine learning to refine it. Over time the system generates increasingly granular customer segments. Digital indicators that the prospect/customer leaves behind (Google searches, a website or landing page visit, sign up for event, request an appointment, sharing on social media) can then expand the data set, enabling you to respond in real time and find new effective ways to engage.
Finding the right CDP for you
There are many Customer Data Platforms and choosing the right one for you is a very important decision. For an in-depth, step-by-step process for evaluating and selecting the right CDP, see our white paper "A Comprehensive Guide to Evaluating Customer Data Platforms."
Step Two Mining and acting on your data
The decision-making function of the CDP enables you to decide what is the best content to send to a given customer over a given time and through a specific channel. Customers and prospects can be scored based on their potential value and a set of business rules and regression models is then matched (using machine learning) to specific messages, offers, and experiences to those customer scores. Then, using the business rules and machine learning, the CDP prioritizes what gets delivered, when and to whom. This allows you to make major improvements in how you engage with your customers by developing more relevant, highly personalized content, within a single channel or across channels, based on a customer's behavioral cues you've collected.
Effective decision making is based on repeated testing that validates and refines business rules and outcomes. Over time, these business rules can become increasingly sophisticated as models and algorithms build on each other, a virtuous data cycle.
Step Three Crafting content for mass hyper-personalization
Using your data to understand your customers and how to engage them has little value unless you have the content to deliver to them. Designing, curating and creating persuasive content and calls to action is one of the most significant barriers our clients must overcome in their automated digital marketing efforts. Just as customer data tends to reside in "silos," so does content ownership.
Breaking down the walls between departments through teams has yielded real benefits. These cross-functional teams continually develop new ideas, design business rules for how to engage specific customer segments, devise A/B tests, and create content. CDP analytics prioritizes opportunities and tags content so it can be associated with a trigger and be ready when needed within your campaigns.
This aspect of the digital transformation and content creation is a critical success factor and is covered in a separate white paper, available here.
The Marketing Technology Ecosystem
Step Four Delivering experiences across multiple channels
Distribution channel systems are simply the conduits that deliver the ad or content to the end user (for example, ad server, or content management platform). Typically, they can be tediously manual and merely blast out communications to wide segments of prospects or customers with little customization. Connecting the CDP engine – with its predetermined triggers and tagged content – to these distribution systems, and a formerly unsophisticated marketing tool becomes a far more sophisticated one, sending specific messages to distinct customer sub-segments across all applicable channels. A library of APIs is available to help tie the CDP into the "martech stack"— the marketing technologies that deliver and track experiences. Integrating the stack this way creates a feedback loop that sends customer response, engagement, and conversion data back into the CDP.
About the Author
Before joining HGS Digital as principal strategist, Robin Snow was founder of Aefinity Interactive, LLC. He has more than 35 years of experience in advertising, marketing, and strategic planning. He has held positions within healthcare as a web center director and interactive marketing director, and has worked externally with healthcare providers as an advertising creative director, marketing strategist, and digital engagement consultant. Over the last 20 years, his specialized experience has been in the planning and implementation of e-health, integrated marketing, and digital business and clinical strategies for hospitals and health systems across the country. Robin was vice president with Greystone.Net for eight years and has worked in conjunction with a variety of healthcare technology companies to plan and implement effective strategic Internet business and communications plans for his clients.