The overflow of information around utilizing big data, creating a data-driven culture and the overwhelming number of Marketing tools emerging daily can really make a marketer’s head spin. Keeping the pace can be tricky, especially when you consider additional factors such as educating teams, achieving buy-in and the challenges associated with implementation.
So, we thought, why not slow down for a second? Let’s go back to the basics and explore the core values of data delivery.
For those new to data delivery, welcome! Today we’re going to take a look at the key differences between data delivery, visualization and analytics tools, as well as recap how to use data delivery solutions to optimize your marketing strategy.
Data visualization tools are wonderful resources for analysts looking to slice and dice data. However, not all executives possess the analytical skill set needed to fully take advantage of their capabilities.
In a previous post on Dashboards vs. Data Visualization, we identify the three paths data visualization are likely to follow:
Data Analytics tools generally give consumers a real-time view of behavior on their website or throughout other owned, earned or paid channels. While reports can often be generated within these tools, data remains siloed in each platform, preventing marketers from seeing a full view of their performance efforts.
Data delivery, however, sits on top of the analytics and data visualization layer. Its main focus revolves around delivering data in a clear, consumable format, to aid decision-making and encourage actions to be taken.
You may be wondering why you can’t just use a visualization or analytics tool to do the above. Analytics guru Avinash Kaushik has put it pretty plainly: “the quest for a single tool/source to answer all your questions will ensure that your business will end up in a ditch, and additionally ensure that your career (from the Analyst to the web CMO) will be short-lived.”
Data delivery tools, unlike the aforementioned solutions, are built specifically to work in harmony with various other tools to deliver stakeholders a single version of the truth. By combining web analytics, social media, ad tech, competitive intelligence, testing, CRM, or sales data, dashboards or scorecards can be automated to deliver powerful, custom performance reports.
So what’s the difference between a scorecard and a dashboard? And why would I favor one type of report over the other? Scorecards are traditionally a progress report full of KPIs that quickly answer “How are we doing?”. Dashboards, however, are more comprehensive and include KPIs as well as charts and tables to give more context to behavior.
The higher up one finds his or herself in a company the less likely they are to need a dashboard. In fact, a scorecard is generally easier to comprehend for those who simply need to track their progress towards as a strategic goal on the fly. Marketers who are responsible for operational tasks, and who must be constantly monitoring efforts or campaigns in order to optimize them, may need to see dashboards containing a much higher level of detail, however. Combining data from various sources into one dashboard that shows not only KPIs that measure progress towards strategic objectives, but also supporting charts and tables that provide context, can give these marketers the information they need to redirect their analysis and explore their data even deeper.
KPIs or Key Performance Indicators, are the true heart of any dashboard. A common rookie mistake, however, is to overcrowd performance reports with arbitrary KPIs that provide little value to dashboard consumers. To avoid this mistake, start with defining your objectives so your marketing team knows exactly what they’re working towards. Next, identify which metrics truly measure your progress towards each objective.
Clearly defined goals give context and structure to dashboards, additionally, alerts keep consumers on their toes as they send notifications whenever data drops above or below a given threshold.
In order to make data that much more actionable, data delivery solutions should provide a space where insights can be managed and teams can collaborate around their data. After all, what good is a report if nothing comes of it? As a stakeholder, you should be able to consume your report, recognize influential trends, and make recommendations to be put into place.
If you have a data delivery solution, yet struggle to make decisions or act on your data, maybe you should consider whether:
The key to promoting data-driven decision-making is to keep processes transparent so that everyone involved has a clear understanding of the mission, relevance of the data presented, and findings. Furthermore, marketers should be encouraged to ask the right questions and explore their data’s behavior in order to make evidence-based decisions.
We’d love to hear about your experience on getting started with data delivery! What factors do you find the most challenging to implementing data delivery solutions in your organization?
Not Another Dashboard.