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A helpful tip in interpreting data is to re-enact how the data was created. This helps understand what the data means, what it reflects and also how you can use it for decision making. For example, for content analytics, revisiting a piece of content. And following the actions that are being recorded. The closer you can mimic the real world method the better. This is a great first step in helping interpret the data that you are… Continue reading
Data-enabled decisions mean you use data to help guide decision making. Data can help provide direction or help unstick indecision, by providing feedback. Itโs worth noting that data just reflects something that has been observed. So it is often not perfect. But if it can help guide and inform your decision great. Continue reading
Embrace data driven decision making as an input in to your marketing. As you shape up your strategy and plans, use data audits to understand what is working and what isnโt working. Then embrace continual optimization and changes through a regular data feedback loop in to progress. This could be real-time dashboards for the tactical through to bigger reports for the monthly, quarterly and annual. Continue reading
First load up the article, pull up your content analytics, then start to look through the data. Does the article perform above benchmarks? Below? Are people reading all of it? Is there a common drop off point? What devices are they reading on? Was it at expectations / above?… Continue reading
Interrogate the data, how was this data created? Is it clean? Does the recording of the data reflect the intention for how you want to use the data. Does it reflect the right date ranges? See if you can find some comparable data, or benchmarks from older data. To help contextualize your data. Continue reading
The first watch out in understanding a chart is looking at the scales. These can be easily distorted to misrepresent findings. Take a chart that is a portrait and make it landscape and it instantly stretches out. So do compare the scales, and the metrics used on each axis. Then explore the data itself, how was it collected, how many data points are in here. Can you draw or add any trendiness? Is the data substantial enough… Continue reading
Data really really helps in analyzing a video. So first stop is to go and get all your data on the video. Then re-watch the video, comparing how you watch it versus the data you have on its performance. Stop where people often stop, click where people are clicking. This will help contextualize and understand what the data is telling you. It may be obvious why people drop off at a certain point. Then you can go… Continue reading
The scope of this could vary dramatically but the basics of a data analysis report include An executive summary, what is that the data is showing us and what did we find. Methodology, how was the data collected Constraints/limitations of the analysis/data, establishing boundaries around the data, how it can be used, what are the strengths and limitations of it. Benchmarks, benchmarks are helpful for contextualizing performance and nuance. Continue reading
When critically analyzing a report, make sure you read it start to finish. Often a nice trick is to start at the back and read all the addendums before you read the actual report. This is often where the limitations or constraints are placed. And knowing these before you interpret the report is helpful. Print it out, get a cup of coffee, get a pen, go to a quiet place. Read it through. Write notes. What surprised you,… Continue reading
A/B Testing is a tremendous practice for marketers to test two different variations. However, it is not bulletproof. First, you need to think about context, what happened before/after people engaged with this A/B test. You want to make sure you havenโt tipped the results one way with a prior A/B test earlier in the consumer experience. Then you need to establish is this a meaningful sample size. For that, you want to look at your overall population of… Continue reading
