Considering how much companies invest in marketing across multiple channels, I’m often surprised that more don’t take advantage of sophisticated tools to measure whether those investments are paying off.
No, I’m not talking about simple analytics that report how many times someone clicked on a banner ad or where a consumer’s last click was before a purchase. I’m talking about data-driven attribution that leverages algorithms to determine how all of an organization’s mix leads to sales. Any exec who wants to know where his money is going and how to adjust tactics to get better results needs advanced attribution to tell him the truth.
Companies that embrace data-driven attribution gain a significant advantage over competitors that rely on last-click or simple rules-based attribution approaches. However, simply purchasing an attribution performance management platform does not automatically and immediately deliver results. It is only one piece of an effective attribution management program. The implementation of the technology itself requires coordination and cooperation across organizational silos: getting access to domain expertise within each impacted organization, ensuring that usable data is being captured, and ensuring that the results from the platform lead to appropriate action.
Here are 10 tips to avoid the pitfalls associated with implementing advanced attribution.
1. Agree on what success looks like: Collaborate with internal stakeholders and the vendor to crystallize what program success looks like. Determine what you expect the program to do that will improve results and how you will measure whether it’s doing that.
2. Gain alignment on primary attribution metrics: Different marketing channels measure, report, and optimize using different metrics, but part of the benefit of advanced attribution is that “results” will be measured using a common set of metrics. Conduct an audit of the existing metrics used in each channel and then establish a limited set of attribution metrics that each channel owner is on board with.
3. Ensure the methodology is well-understood: Humans are skeptical of things we don’t understand. Educate stakeholders so they recognize that the power of attribution management comes from a complex but comprehensible approach. That goes a long way toward turning passive and skeptical stakeholders into vocal advocates.
4. Explain the realities of data capture: Attribution management platforms are not omniscient, so there will be data that is simply not available. Being open about what will and will not be included in the initial rollout, as well as educating stakeholders that the goal is actionable attribution rather than perfect attribution, prevents the program from being undermined.
5. Bring in IT well before the contract is signed: Your IT organization will be involved in the implementation of the program; they bring valuable knowledge as to how and where your data lives, and how it can most effectively be integrated into the program. Engage the right members of the IT organization early and often, and the implementation and ongoing maintenance will go much more smoothly.
6. Expect to modify your existing data sets: Although you are already capturing data from your Web analytics platform, paid search platform, media platform, and numerous other places, you will still need to make adjustments to these platforms. Work with your vendor early to identify where these updates need to occur, and engage the appropriate parties as early as possible to get those updates in place.
7. Engage channel owners early and often: Advanced attribution shifts the way an organization understands its marketing mix, which can be unsettling. Involving channel owners throughout the implementation, encouraging questions, asking for input on implementation decisions, and regularly assessing the skepticism level of each of these stakeholders will enable you to proactively engage them and address their concerns.
8. Establish a process for taking action: Ultimately, the program only has value if it leads to action. Develop scenarios using sample deliverables that match what will be available after the implementation is completed and work through them with your stakeholders: Who would take action based on these results? What action? When?
9. Establish a data governance plan for the program: While there will be an initial push to get all of the data flowing to the platform for the initial launch, data sources will evolve over time. Formalizing the governance of the data–where it lives, how it is integrated, what will trigger changes, and how those changes will be communicated–early on minimizes the chance that the data will suddenly “break” at some point down the road.
10. Establish regular program results readouts: Implement a way to clearly summarize the performance of the program on a recurring basis, including both the success measures established at the outset, as well as specific actions that have been taken based on results from the program.
With marketing budgets increasingly being squeezed, success requires taking advantage of the best tools available. Encouraging your team to become one that has the experience, communication skills, technical knowledge, and enthusiasm to build a successful marketing measurement program can be a challenge, but it is a challenge well worth taking.
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