Using data effectively remains a priority and a challenge for marketers. 

Data-driven personalization campaigns and customer interactions are falling short. This isn't an issue of a lack of data, but rather an overabundance. 

So how can marketers tackle this challenge in order to drive successful campaigns across all platforms? How can they set goals to assure success?

2016 saw an improvement in data driven, triggered emails that also utilized segmentation. The problem is that this is just one channel. Companies are still failing to prioritize multichannel in their marketing strategy. 

Centralizing data and making access to this data and content easier should be at the top of every marketer's to-do list. Acting on the following three trends will help any marketer move their strategy forward.

Multichannel Marketing Success Depends on Data

Multichannel marketing has helped brands achieve better results and stronger customer engagement. According to one study, 72 percent of consumers prefer connecting with brands through an integrated multichannel effort. And the benefits aren't limited to the consumers. Another report found 50 percent of multichannel marketers “usually” or “always” hit their financial targets. 

Multichannel marketing is a three step process. Performing a data audit is your first step. Establish what data you collect and how you collect it. The audit will inform your data strategy, where you define how you will manage and apply all that data towards marketing efforts. 

Next, identify any technological or organizational hurdles standing between you and multichannel success — how will you resolve them? Finally, start testing. Start with campaigns that span only two channels to learn the process and understand performance before moving on to more complex campaigns. 

How to take action: Start small. Pick a small target group and test a campaign with two channels to begin with. Measure the results, identify correlations between both channels, improve small items, learn from the outcome. 

Then slowly increase the size of the target group. Once you have a grip on dual-channel campaigns, add a third channel.

Learning Opportunities

Machine Learning and Marketing Automaton: A Marketer's Best Friend

We are inundated with data — but that's OK because we've got machines to help us out. 

The number of new machine learning tools and vendors emerging allow for greater customer insights, better analytics and real-time decisioning for message and offer-selection. The beauty of these machines is they let us know what we should do next and remove any doubts in the equation. 

Machine learning is the answer to every marketer's dream, by putting the solution to the data problem at our fingertips. 

How to take action: You need to focus. Start by defining one problem you would like to address. Machine learning efforts need the right data to support their efforts. I recommend you start simpler, and then move to more advanced areas such as real-time content selection and optimization across multiple segments. Build your action plan slowly and steadily, but keep the long-term view of ROI in mind.

Improved Data and Result Visualization

As visually-driven beings we interpret data and content better through visual representations. Your goal is to give your audience — in this case your marketing team — a better way to understand the information at hand. Putting this data in the hands of marketers makes everyone a stakeholder in your goals — and hopefully we'll see more tools incorporate multichannel data to better inform the end users. 

How to take action: Focus on data quality as this will reflect in your data visualizations. Note what information internal stakeholders need to see in order to create visualizations that reflect everyone's needs. Remember, an effective data visualization should promote easy customization of the most commonly needed data and performance points.

Put Together All the Pieces

Digital marketers are poised for even greater results in 2017, through a combination of strategic thinking, technological advances and improved use of consumer data. To pull all of these pieces together, we'll need to overcome hurdles around cross-channel integration, organizational structure and resourcing constraints, while balancing consumer needs and expectations. Take courage — it can be done!

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