Digital Governance: Best Practices from the Trenches
For the past three Adobe Digital Marketing Summits, I’ve hosted a breakout session focused on digital governance (also referred to as web governance), which focuses on how companies can successfully manage their digital analytics and optimization programs to drive business value. As most organizations have come to realize, it takes more than just technology to be successful with web analytics and testing – it requires an investment in people and processes as well.
No company can simply turn on a new web analytics tool and expect to become data-driven overnight. Attitudes need to be shifted, processes need to be adjusted, positions need to be staffed, and executive support is essential. While the rewards are great so are the challenges; therefore, companies need a strategic roadmap or game plan for how they’re going to create an environment where analytics and optimization initiatives can flourish. The goal of this year’s session was to provide structure to that roadmap and start the process of targeting and prioritizing what needs to be addressed.
This breakout session featured a roundtable discussion where industry practitioners could share their unique perspectives as well as best practices that they’ve identified and implemented at their companies. For many of the participants it was a great opportunity to network with their peers and learn that other people are facing similar challenges (sort of like group therapy). Like I’ve done in past years, I’ve asked the volunteer moderators to share some of the key takeaways and themes that were discussed within each of their roundtable groups. I’ve consolidated their notes into the following key points:
Strategy
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- Executive team should sign off on the recommended strategy, confirming they are in alignment
- If an analytics team is unable to get ample input and guidance from above on the online strategy, they will be stuck with in-demand, short-term or tactical reporting (not ideal)
- Unclear and conflicting goals (both between and within teams) as well as stakeholders striving to protect their existing resources and power create headaches for digital analytics professionals
- Strategy review sessions with all of the stakeholders are helpful in shaping a clear, accepted strategy
- Collaboration software and lots of casual conversations across teams were also helpful
- Ensure the business requirements and KPIs are well-defined because what is requested by the business may not be what is really intended or needed
- Always anticipate the inevitable follow-up questions that were not in the original requirements – otherwise you’ll under-deliver and always be playing catch-up
- Business strategy should still guide decisions around what online or offline data is truly necessary
- What can be and should be measured are two different things
Executive sponsorship
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- Create an environment where top-level executives feel like the findings were a result of their efforts. Once they take ownership, things will get done faster and they will persuade others to support the analytics initiatives
- Executive sponsors play a key role in helping to define/clarify the strategy, prioritize projects, get people to use and trust the data, and drive more accountability
- When you don’t have executive sponsorship for your analytics program, you need to build support at a grass-roots level, generate a list of monetized quick wins, and evangelize your successes across multiple levels within the organization (especially at the C-level)
- Executive sponsorship can go both ways – can remove roadblocks or create a “I want this” mentality which becomes more of a distraction
Reporting and analysis
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- Change the mindset and focus of your analytics team (“We don’t do reporting, we do analysis”)
- Outsource low-level reporting to non-strategic resources (third-party) so analysts can focus on projects that are strategic to the business
- Too much data or information can overwhelm internal customers to the point where they can’t digest and use what’s being shared
- Interview or survey your internal customers on a regular basis, verify what they’re interested in, and determine how it can be best shared in a meaningful way
- With context being so important, create a “dummies guide” or cheat sheet to guide end users through how to interpret and use the data and reports properly
- In order to avoid data interpretation issues, have new users complete a training session on the analytics tools before being granted login access
- Accountability is often challenging when working with agencies, which sometimes spin their results
Impact of turnover
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- Need to revisit teams, especially when there’s significant turnover, to ensure the new team members are aware and up-to-speed on current processes
- Turnover among executives can change business objectives and KPIs so the measurement strategy needs to be proactively re-calibrated
- Measurement strategy should be firm, but also flexible enough to shift with changing business needs and organizational structures
- When turnover is high for seasoned analytics talent, you should invest in training entry-level applicants and building them up over time
Process
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- Make sure the measurement strategy is understandable and will support repeatable and manageable processes
- Over time whittle down those processes that don’t contribute to data completeness and integrity
- Modify those that were defined to meet the changing realities of the business
- Politics and bureaucracy can impede on executing recommendations so you need to have a defined process in place (e.g., “when x happens, we will do y”)
- Prioritization is essential when you’re dealing with limited bandwidth and headcount so that you’re maximizing your impact by focusing on what’s the most important to the business
Implementation
- Most data problems are caused by new development projects so make sure the analytics team is aligned with the development/implementation team, especially for the QA process
- Leverage standardized forms for new deployments so that the development team knows how to read and implement the requirements correctly
- Don’t forget to show the development team your findings because connecting their implementation work to your analysis will make them much more likely to prioritize future tagging requests
Testing
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- Marketing teams need to move beyond testing approaches (running the same tests over and over with the same results) into “learning” and “best practices”
- Create a centralized test lab that can corroborate results and lead the learning across marketing teams
Monetize impact
- Sell your analysis by monetizing the impact of your recommendations
- When you attach dollars to your reports and analyses, C-level executives will be more apt to acknowledge the findings and act upon them
- In order to get better and more advanced analytics tools, you need show the monetized value of your existing analytics tools through various documented wins
This was only a sample of the insights and takeaways that were shared during these roundtable discussions. If you’re still hungry for more insights on this topic, you can check out key takeaways gathered from the previous Summit roundtable discussions from 2010 and 2011. If you participated in the roundtable discussions and one of your key takeaways wasn’t captured in the above summary, please feel free to add a comment to this blog post. I’m sure all of us would love to hear what takeaways you had from the session. As I stated in my presentation during this session, no organization has digital governance all figured out. While some organizations may be further along in certain areas, all of us still have room to learn from each other. Hopefully, by sharing these types of insights, collectively we can become stronger and better in our craft, driving more value from our analytics and optimization programs. Lock and load!
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