Developing A Data Road Map: How To Implement A First-Party Data Blueprint
Once you've learned the basics for creating a first-party data strategy, it's time to move on to the next step. Columnist Mike Sands walks you through building a data road map and the initiatives needed to reach your goals.
Marketing is an increasingly data-driven discipline. Brands have an abundance of data from their customer interactions via the Web, mobile, email, in stores, advertising and more. And notably, research shows that marketers reporting the most success are doing the best job of harnessing and using this customer data — their own first-party data — to drive analytics, personalization, targeting, audience segmentation and the customer experience.
In my last column, I outlined three steps to help marketers start with the basics in building a successful first-party data strategy: conducting a data audit, defining objectives for meeting business goals, and identifying the data points necessary to meet those goals. For many brands, the ultimate objective is creating a centralized foundation that allows them to connect fragmented customer data, resolve cross-channel identity, and take a more holistic marketing approach.
Once marketers are aware of the current data landscape at their fingertips, what comes next?
1. Build A Data Road Map
Having documented their baseline, marketers can begin to build a road map of what they need to execute to achieve their strategic data-driven goals. This is an actual document that includes several deliverables and will serve as a blueprint for the organization’s implementation of data initiatives, as well as an action plan that diverse global teams can rally around to execute.
These deliverables include a “desired state” and how it maps to strategic objectives and a gap analysis report. They also should include a detailed road map of initiatives needed to reach the desired state, including people, process and technology considerations (in three flavors: conservative, realistic and optimistic), and an ROI analysis. You should consider making a formal presentation of this road map to the stakeholder team.
Typically, brands fall into two camps as they try to solve highly complex data-driven marketing challenges. One way is to bring in every possible internal stakeholder and purchase all-encompassing enterprise software. This can be like trying to “boil the ocean” — it can take years to complete and isn’t in line with today’s speed of innovation.
The opposite strategy focuses on point solutions and hones in on very specific problems. For example, a department may be incentivized to address narrow attribution issues such as how display media is affecting sales — instead of taking a higher-level view that looks at data across multiple teams to learn about how customers shop.
The best strategy is to find a happy medium between the two above scenarios. A detailed data road map will help determine a tangible set of accomplishments that can be done in a defined, reasonable amount of time.
2. Define Short-, Medium- And Long-Term Goals
Creating a data road map and organizational data foundation is best tackled via incremental initiatives that generate ROI or hit key markers along the way. So marketers should make sure to identify their own tangible objectives based on the marketing organization’s short-, medium- and long-term goals.
For example, many marketing organizations set out to improve areas such as personalization or customer experience. Breaking that down to what’s achievable in the next three or six months, and then beyond that time frame, will surface more tangible objectives.
For example, converting one-time purchasers into repeat shoppers can be something to be tackled in the next six months. That project then leads to a more comprehensive initiative to move customers from a lower-value loyalty segment to a higher one through a mix of media and on-site personalization.
3. Evaluate Potential ROI, Phasing, and Investment Priorities
Marketers should understand and identify key marketing initiatives that will offer the most ROI in the shortest period of time. Remember, it isn’t possible to transition from the current state to cross-channel marketing success through one massive technological leap.
Instead, it takes smaller, incremental steps as various technological options are tested. That done, you can settle on what works best for your brand and innovate from there.
A gap analysis will identify granular steps the organization needs to take related to data and its supporting technologies in order to move forward and meet its strategic objectives. A solid first step might be to tailor messages to loyalty program members’ emails according to their level of spending or lifetime value. If there are increases in lifetime value after a fairly short test period (e.g., three months), a subsequent step to continue building on the ROI of this initiative could be to partner with a retail chain to better understand a particular high-value segment’s spending habits.
The Power Of First-Party Data And Identity
The data audit and road map are key steps toward building a centralized customer data foundation to optimize your support for your cross-channel budget and marketing programs. It’s no easy task, but it’s well worth the effort.
Resolving a customer’s cross-channel identity — discovered by leveraging first-party data and merging activity across multiple channels and devices — is a valuable asset you can use to improve marketing measurement, personalization, messaging, and ultimately, a customer’s overall experience.
Stay tuned — in future columns I’ll explain more about aligning your organization around a cross-channel data strategy, harnessing live intent signals, and enhancing your first-party data with CRM data.