To start leveraging your CRM data, take these key steps.

1. Target campaign to customers’ attributes: The more you know about what your customer “looks like” the more successful you’ll be. Dig into your CRM data to find trends in attributes including past purchases, affinities, demographics and other characteristics of your existing customers. As well as showing you which customers convert better, this enables cross-sell and up-sell opportunities.

Create a CRM segment of customers who purchased within the last seven days, and create offer “A” (an extended warranty, maybe). For another segment who purchased more than six months ago, create offer “B.” Your CRM insights are now keeping you relevant, avoiding the risk of alienating customers through mistargeting.

2. Segment to Deliver Results: Onboard your CRM segments into your online marketing platform and deliver across multiple channels. You can run your custom campaigns across ad networks, social media and your own website, creating a consistent, personalized dialogue and customer experience. Use real-time analytics to see what is working or not.

3. Optimize and extend: Now, use your CRM data to extend your customer base. Take what you know about your high-performing customers, overlay it on third-party datasets, and build lookalike audiences of prospects who share your top customers’ attributes. If you know that a particular income level combined with ownership of a certain car model are top customer attributes, create a custom audience of prospects based on this. Compared to targeting a generic audience… well, as our research shows, there’s a league of difference.

4. Don’t forget to scrub that data: Make sure that your CRM is complete, up-to-date, and accurate. That means name, address, phone number and email at a minimum. Whether you interact with customers in-store or via call center, this information is essential for a personalized experience that makes customers feel valued. It also helps you quickly identify and spend time with high-value customers.

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Marketers need to adopt a new definition for marketing automation, one that includes both the automated components and that recognizes that marketing automation is a process that marketers must manually initiate.

Advanced/ Digest...

Marketing automation refers to the process in which artificial intelligence and predictive analytics are used to automatically deliver and manage custom advertisements or communications to the person most likely to take a marketer's desired action.

Breakthroughs in three key areas are leading us to a point where this new definition moves beyond concept and into action.

1. Artificial Intelligence: Seamless integration of customer data, data warehouses, and data augmentation providers are enabling knowledge extraction through advanced data mining. This allows marketers to not only leverage their existing data but quickly take action on new data. 
2. Predictive Analysis: By implementing machine-learning, marketers are presented with preset audiences that combine propensity to complete desired actions with core attributes of optimal channels, products, and ads/content. This preset audience is then paired with an advertisement or piece of content and awaits deployment based on the opportunity to reach the person at the optimal time. Programmatic buying platforms activate this approach for search marketing, social media, display advertising, video advertising, and mobile advertising. 
3. Deployment and Management: This is becoming the "high-frequency trading" of the marketing world. As algorithms and automation enable marketers to reach target audiences with speed and precision, competition drives the race for the most relevant ads and content at the optimal time. This leads to further emphasis on the prediction of trends and forecasting of results. The marketers who "win" will be the fastest moving, most precise, with an ability to shoot where the target will be, not where it is. 

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Advanced/ Digest...

Prediction #1: Beyond Dashboards

[Marketers] will ask data specific questions for the insights to make time-sensitive business decisions. Why is this so important? Current-state reporting tells you what has already happened, but does not reveal what the marketer really needs: insights into why consumers make the buying decisions they do. Advances in analytics technology AND marketers' acceptance of it will deliver data not just on the "what," but also the "why," the "when" and the "what if" for true decision support.

Prediction #2: Right-Time Marketing

Right-time marketing will become more and more common as businesses are able to combine and make sense out of consumer breadcrumbs across all channels of engagement in a timely manner. This next-gen approach, however, will require access to real-time, granular multichannel data across all channels, which can then be analyzed in real time to reveal hidden relationships and shed new insights into critical business decisions.

Prediction #3: Marketers as the New "Quants"

As marketers begin to understand their data and begin to predict behavior, they will be more like the "quants" on Wall Street with automated trading algorithms - but with one caveat. New tools will enable not just the "data scientist," but also the average marketer to easily create forecasts, determine optimal approach, automate all necessary consumer-facing actions, observe actual outcome, learn and repeat for improved results!

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