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How To Begin Leveraging Your First-Party Data By Understanding The Landscape

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Known only a few years ago as “digital” consumers, today’s customers are now “always on” thanks to the ever-increasing use of multiple connected devices throughout the day and on the path to purchase. At the same time, consumers expect a greater level of consistency in their experiences across physical and digital touchpoints — making the need for a unified marketing strategy imperative.

It is no longer sufficient to rely on tags and cookies to track and reach users on the Web, while relying on entirely different strategies on different channels. Instead, marketers must now be prepared to measure and respond to consumer behavior in real time, on any channel, in order to maximize their likelihood of influencing a conversion.

This requires a new approach to the way that marketers conduct campaigns and initiatives. Rather than chasing the next shiny object that promises to reach consumers in a unique way, they should first prioritize the collection and analysis of data as a discipline that underscores all marketing activities.

With a solid foundation of first-party data, reaching consumers across channels becomes far more efficient, accurate and effective. In fact, a recent survey from Signal (my company) and eConsultancy found that marketers with the highest returns on their data-driven campaigns are already using first-party data at a much higher rate than their peers.

So what are the keys for success in harnessing the power of first-party data? The reality is that senior marketers need to start thinking about data as a discipline and a priority. There are clear things they can do to make sure that their teams progress along the data maturity model and tie marketing results to concrete business objectives and outcomes.

To get started, marketers need to create a baseline from which to build their first-party data strategy. Here are the three steps to an effective current-state data analysis:

1. Conduct A Comprehensive Data Audit

The first step to gaining an understanding of a company’s data landscape is to catalog and classify all relevant data points, their sources and how they’re being used — in other words, a data audit.

In many instances, different marketing initiatives across different teams have created silos with varying levels of sophistication and scale when it comes to acquiring and collecting customer data. Auditing data will help to break down those silos by creating a single database of sources.

Also, and this may sound simple, but it’s critical to ensure consistency in the way that terms like “impression,” “lead” and “conversion” are used. One team’s impression could be another team’s lead, which will create problems when everyone is being measured against the same criteria.

Ultimately, the result of this step should be a single table that catalogs all data points and clearly defines key terms.

2. Clearly Define Objectives

Defining objectives means going beyond an overarching goal. “We want to have the best cross-channel capabilities in our category,” for example, is a great goal, but it doesn’t help achieve anything. Therefore, it’s important to break broad goals down into actionable objectives that provide a road map toward the final goal.

Let’s take an e-commerce retailer as an example. One objective might be to turn more one-time buyers into repeat customers. This objective, as opposed to a broad goal, is narrow enough to make achieving it far more feasible within a given time frame.

This process should also involve key stakeholders. Sit down for meetings with the leads across various marketing channels in order to get a sense of their most immediate needs and objectives. This will further inform the road map to success by identifying opportunities to quickly and positively impact revenue.

3. Don’t Forget What’s Missing

The flip side of understanding what data points are currently available is identifying the necessary data points that are missing. For example, a company might be hoping to target a product to recent college graduates but has no way of determining that characteristic using existing data points.

Once gaps in the data are identified, the fastest way to address them is by working with a third-party data vendor. This requires a rigorous analysis of potential vendors in order to determine the best fit.

Once that’s accomplished, marketers shouldn’t settle for stock segments like “soccer mom.” Instead, they should ask questions about the quality, sources and freshness of the data to see if it fits their specific needs.

Once the full current-state data analysis is completed, marketers will be well-equipped to tackle the challenges ahead. A successful data analysis will have clearly identified all currently available data points, sources for any missing data points, and the objectives that a first-party data program will accomplish.

Consumers and marketers alike have demanded greater consistency and faster reactions ever since the launch of the first iPhone in 2007. Today, we have the capacity to address those needs — but it requires a concerted effort with key stakeholder participation.

Stay tuned for my next article about the second step in harnessing the power of first-party data: creating a data road map. The road map will help marketers determine the “desired state” of their first-party data strategies, get stakeholder agreement on that desired state, and then outline initiatives needed to reach their goal.

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