Alight Analytics ChannelMix

Analytics Big Ideas – What You Should Already Be Doing

Times are changing, and with change comes opportunity! One of those inherent opportunities is in the analytics space. Data quickly can serve as the heartbeat of any marketing campaign, but is only as valuable as we set it up to be. Questions from clients and leadership teams will continue to become increasingly more difficult and sophisticated, so there needs to be a fundamental shift of seeing data as a utility instead of a luxury. The narrative or storytelling component of analytics is where value becomes apparent and having actionable insights to share with clients or leadership teams depends on the best practices put into place upfront.

To set yourself up for success, you should make sure that your organization:

1. Has a defined measurement framework. Evaluate successes based on trackable and measurable actions that occur pre-, during, and post-campaign, and have a tangible impact on business objectives. Set upfront goals to pace against and allow for increased transparency. What key business questions are you wanting to answer? What gaps have you identified? Ask yourself questions to better understand what metrics you need to be tracking.


2. Has an automated data aggregation process and systemwide alignment on data. This will be critical to ensuring that you build processes that are replicable, sustainable, and scalable long-term. Automation will allow your organization to be data-driven in decision making and be proactive as opposed to reactive with those decisions. When we approached automating our data aggregation process at Infinity, we partnered with Alight Analytics and their platform, ChannelMix, to help us tap into automation across over 150 different sources. This automation has allowed us to focus on data strategy across our whole data ecosystem and has led to a systemwide alignment on data. Automation leads to efficiency and that’s what we should be aiming for with analytics. Predictive analytics is continuing to emerge as a key differentiator. If you don’t have quality data, you can’t get to predictive insights. Automation helps you get there.

3. Has a data visualization strategy. Once you have the data automated, the next step is to visualize it in a way that is easy to understand and is directly catered to goals and objectives. Eliminate clutter – be intentional with what you show. If it’s something you can’t take action on from an optimization standpoint, don’t show it unless it’s related to the larger goals and objectives. We’ve found that building out interactive dashboards in Tableau has worked for us and our clients. To learn more about how to build a high quality marketing dashboard, you can check out one of our other blog posts:


4. Has customized processes and solutions in place. A one-size-fits-all cookie cutter approach to analytics won’t work short-term or long-term. Each internal team or client will require a customized approach tailored to unique needs. This correlates back with making sure that key business goals and objectives are applied to the data strategy and data visualization processes and that every piece of that from strategy to insight generation is tailored to its intended audience. For example, an executive summary capturing how the top 5 metrics related to overarching business goals for the year would be something the C-Suite would be into, while marketing managers may want to see more granular information about different types of creative or messaging.

5. Has a process that is as dynamic as the changing landscape. The marketing landscape is always changing and evolving. One of the biggest hiccups in the status quo will come from limitations in targeting opportunities across digital platforms that will impact reporting metrics. It’s imperative to have solutions in place to anticipate data privacy and targeting limitations from PII and third party data in digital – Chrome will block 3rd party ad cookies within the next few years and we will need to solve this problem before it’s even in its infancy. A lot of this will come through strong data management practices, but throughout the whole strategic planning process, it’ll be even more important to understand how digital marketing platforms work with other platforms like Google Analytics and CRM systems. You can establish custom goals and events in Google Analytics that will better understand more about customer intent and what behaviors are occurring across referring sources. CRM systems help to track the full customer journey and associating downstream activity. Identifying new ways to think about tracking and utilizing data that you already have at your fingertips will be vital once these sweeping changes occur.

Analytics and data have never been more accessible than they are now.

That’s why it’s important to get best practices in place as soon as possible. Why is analytics so important? The data that becomes part of the analytics process helps organizations optimize performance and business outcomes, even beyond marketing! Insights from the data help to optimize marketing efforts for better performance, and help to maximize the budget by identifying the most efficient and effective marketing opportunities.

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