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  • Writer's pictureDavid Avery

6 Common Mistakes When Doing Marketing Analytics

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Most marketers know the importance of analytics. Whether it is for channel optimization, identifying customer segments or planning campaigns, optimizing marketing efforts is critical for any business. According to Invesp, leveraging data-driven personalization in marketing campaigns can deliver 5-8x the ROI.

However, the lack of knowledge about these common mistakes leads to wasted money and ineffective campaigns that disappoint marketers and customers alike! Many marketers are misusing data and, as such, don't receive the benefits of analytics that maximize their marketing return on investment.

If you want to become a data-informed marketer, these few tips will help you avoid these 6 common mistakes when doing marketing analytics.

Article Content:

Not setting goals marketing analytics, objectives, and metrics.

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This should be an obvious one, but so many marketers out there do it! If you don't have goals/objectives defined before you start measuring your metrics you are just wasting time and effort in telling your business to do something without knowing the desired outcome. This may make sense for some marketers (i.e. - "increase traffic"), but not all of them.

Creating your goals and objectives, and setting up the metrics that need to be track greatly varies based on the type of business you are in, the type of campaign you want to run, and the tools that you use. Without these goals to measure your success, marketers waste time on meaningless metrics like "traffic" or "likes".

Many marketers fail to realize that their data is only valid if it aligns with their marketing plan. If the plan isn't aligned with the data, then there is a problem. There are many reasons why we might fall into this common mistake when doing marketing analytics:

  • Lack of training: If you are new to analytics and have little or no training, then deciphering the right information from data will be a challenge. Most don't realize that there are more than just "answers" in your data. Instead, they focus on what's statistically significant, which may skew results.

  • Not understanding how things work together: You can't just build a dashboard and expect people to figure out where everything goes and for what reason it is there. The first thing should be talking about the dashboard's goal, then explaining how each visual supports that specific goal (like showing conversions, traffic metrics, etc.).

Giving too much attention to one area

All marketers inevitably make mistakes, but a common one in particular is focusing too much on one metric or strategy. It is okay to want your campaign/metric/strategy to succeed, but don't let it get ahead of itself. If you spend too much time trying to optimize a metric that is already doing well, you are going to miss the bigger picture. Analytics only show small pieces of a much larger strategic puzzle.

For example, if you are running an e-commerce website and one goal that you have set is to increase sales, then don't focus on only that one goal. Are you measuring the success of your content marketing? Do you know if it's reaching the audience you want to target? What about SEO or paid search optimization, are they achieving the goals that you have specifically for them? Depending on how much time and effort goes into these other strategies, it could help or hurt your overall goal of increasing sales. Similarly, if your company has a small budget for marketing strategy implementation; there can be no way to track every aspect at once without losing money in processes due to redundancy.

There are many ways you could avoid this common mistake when using marketing analytics:

  • Make sure that your metrics aren't solely on "how may visits" or "unique visits": It's not just about how traffic looked around the start of your marketing strategy. You should also be looking at how the trend looks over time, as well as what they are doing on each visit (i.e.- purchasing, navigating the site).

  • Avoid solely relying on a social media or organic search campaign if you have other options: Every business is different and you can't just assume that one will do better than another unless you test it out.

  • Understand how things affect one another: If your marketing strategy requires customer service, then it is important to know how the two influence each other. What if a customer can't get through to you and becomes so frustrated that they go to your competitor instead?

Optimizing the wrong metric

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Just because you want to optimize something doesn't mean that it is the right metric for optimization. The whole point of analytics is to help improve business performance by increasing relevant metrics, and this may include optimizing a certain part of your marketing efforts by cutting down on unnecessary parts. If you choose the wrong metric to optimize, this could heavily impact your marketing campaign and lead you with a loss of performance.

For example, let's say that you want to optimize sales on your website, but your analytics shows that a large portion of sales are coming from traffic driven through paid search ads. You could cut down on those costs thinking that it will have an overall positive effect on revenue generation, when in reality cutting down on these would mean abandoning traffic source with high conversion rates. To avoid this mistake when doing marketing analytics, make sure to really understand what each metric represents in terms of value for your business (such as what is working, what isn't working, and why), so you can allocate resources efficiently as well as identify areas for improvement whenever needed.

Using only last touch attribution modeling

Marketing channels and campaigns are not directly responsible for revenue generation, but they have the potential to influence customers' behavior at crucial moments of the purchase process. Only using last-touch attribution modeling misses most of the revenue generation opportunities that are embedded in different marketing campaigns and channels. It is more likely to be closer to reality if you only measure your last touch for a specific campaign or channel, but measuring both your last and first touch would give a bigger picture of what really happened during the purchase process.

Alternatively, a good practice is to use customer lifetime value as a measure of performance where the final purchase outcome from each touch point can be attributed to previous interactions with relevant channels or teams that contributed at some point of the purchase journey (directly and/or indirectly).

Selecting the right attribution model to use is important since it gives marketers a clearer picture of how different bits and pieces of their marketing efforts are contributing to revenue generation. Make sure that when you are choosing which model to use, you are picking a model that reflects your business' most sought after value.

Ignoring seasonality

It is easy to neglect factors like time and season if data samples are large enough, which may lead an analyst to faulty conclusions. You should consider seasonality of the business cycle/industry, weather variation, or trends in order to understand what contributes to success or failure at different times of the year. For example, if you have a sales promotion that runs in the beginning of the year but does not run at all after January and will not be part of your ongoing strategy for the rest of the year, then there is a big chance that you are missing out on opportunities (or worse, including unnecessary costs) that could help increase revenue generation. By focusing on metrics that do not vary as much from season to season, you will get a better understanding of how different marketing efforts are contributing to your business at any given time.

One way to solve this problem is by using a time series analysis approach (such as ARIMA) where seasonality can be easily identified and corrected for. This way, you will be able to get a better picture of the performance of your marketing efforts throughout different periods during the year.

Another way to help identify seasonality is by using visualizations like line graphs, bar charts and scatter plots to indicate how your KPIs (such as conversion rates) change over time for different time frames (i.e. day, week, month and quarter).

Not acting on what you learn

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Failing to act on what you learn from your analytics is just as bad as not doing any marketing analytics at all. It may lead you to making the same mistakes over and over again, which will eventually cost you in terms of time, money and resources wasted.

One way to solve this problem is by setting up a process that will help you learn from what your data tells you every step of the way. This process can be made to work with your current marketing and analytics strategies, such as by implementing learning loops or a feedback loop to help you maintain continuous improvement, so that everything you do in terms of marketing is a step towards achieving your business goals.

Another way is by setting up dashboards that will track progress along different metrics (such as conversion rates and cost per clicks). This will help you measure the effectiveness of your strategies right away and make any necessary changes in real time. By doing this, you will be able to adjust the way you market your business as well as make sure that everything you do is part of a larger strategy and contributes towards achieving your goals (unlike just releasing whatever comes to mind with no consideration at all).

Remember that the main goal of doing marketing analytics is not just to get insights but also to actually act on them as they come up with an actionable plan. Whether it's questioning your assumptions, setting specific goals, or finding out ways to actually measure the effectiveness of your tactics in terms of business impact and ROI, as an analyst you should always be thinking about how you can use what you learn from your data every step of the way.

Key Takeaways

There are many common mistakes that people make when doing marketing analytics. One of the most important things to remember is not just getting insights but also acting on them and making sure your strategy includes a process for continuous improvement. The main goal of doing market analytics is not just getting data, it's taking actionable steps towards achieving business goals. So, don't forget about how much time, money and resources you're wasting by avoiding implementing any changes based off what you learn from your data!

Optimax Business Consulting can help you avoid these marketing analytics mistakes by providing the right advice and strategy to help your company realize its full potential. Schedule a free 30-minute consultation today!

Join the conversation: What do you think is the most common mistake? Which have you done? What would you add or subtract to the list?

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