The power and potential of web analytics has increased tremendously over the last years. But many businesses keep using it in the same old ways – missing out on valuable growth opportunities. Proactive Analytics is a method for bringing your analytics game to the next level.
Right now, your team is most probably already using Google Analytics. Perhaps you’re using it to track your traffic or events and to create marketing reports. And then, you may be using the data to validate marketing spend, visualize trends, and export audience lists.
This is all great and has been a common practice ever since web analytics became a commonly used tool. But since then, the power and potential of web analytics have evolved more than many people are aware of.
If you’re using your data in the same old way you always have been, there’s a real risk you’re missing out on great opportunities to improve your business.
A more proactive way to use web analytics
The problem with the way most businesses use analytics today is that it’s more reactive than proactive. Many companies monitor what’s happening and react to it, instead of using the data to take action.
For example, when was the last time your company defined a business objective, created a testable hypothesis, and then tested the hypothesis using analytics? If you’re not currently using your analytics to drive your plans for progress and innovation, keep reading.
To fully take advantage of the possibilities that come with modern web analytics, we have developed a new framework and methodology. It’s a strategy that any organization can adopt, and that can almost run by itself, with very little need for change management.
We call this methodology Proactive Analytics.
Instead of treating analytics like a read-only report, Proactive Analytics enables you to use your analytics to drive action and actively progress towards achieving your business objectives.
What is Proactive Analytics?
Proactive Analytics is a 7-step process inspired by the Lean Methodology; a framework initially developed and perfected by Toyota to use in their factories in the 1930s.
We’ve found that the same principles are useful in general business practices, and especially when it comes to digital analytics and data.
A lean approach applied to web analytics
The Lean Approach is a methodology that involves three key steps: Build, Measure, and Learn. In this approach, the time it takes to cycle through these three steps is minimized to ensure that a company is continuously obtaining validated learning. In the context of digital analytics, this allows for each new feature, campaign, or design change released to be measured against key metrics and business objectives.
The lean approach is an ideology of iterative product releases to allow for data-driven attribution. For example, if an e-commerce company adds five new features after several weeks of development and finds that their total sales have increased, how will they know which exact feature led to the increase?
By continually testing business hypotheses through a data-driven approach, a company can pinpoint what exact features of their product are working. This can inform future innovative decision-making so that the business is producing what the consumers really want.
At the core of Proactive Analytics is your campaigns. A campaign is any activity that you perform to achieve the business objective. It can be a marketing campaign, a new feature release, a new user interface design, or a blog article, just to name a few.
Proactive Analytics turns digital strategy upside down
Traditionally, digital strategies tended to be more reactive than proactive. Marketing campaigns were launched, and their metrics were measured to judge success.
With the Proactive Analytics approach, the digital strategy starts with a specific business objective, followed by creating a campaign or feature to achieve that objective (in other words, the hypothesis). Lastly, the results are measured, and a definitive conclusion is reached.
The main parallel between Proactive Analytics and Lean Manufacturing is that you can scientifically test campaigns or features to see whether and how they impact your business objectives: positively, negatively, or not at all.
This methodology enables cross-team collaboration around data. The decision process becomes transparent and data-driven. Rather than communicating with your marketing teams only through weekly or monthly reports and dashboards, you can have them perform scientifically provable campaigns involving other departments.
And remember, a campaign isn’t necessarily just an online advertisement. It can be the release of a new feature, function, or updated design on a website. It could even be a content strategy such as email marketing campaigns, blog articles, or video content that drives unique engagement and brings new traffic. If your company has been wondering how to become more innovative, this is your answer.
Let’s say you’re an e-commerce company who would like to increase sales of your laptops. You’ve identified two buyer personas: young gamers and business professionals. Your target is a 150% increase in sales revenue from laptops. You decide on a few potential campaigns:
- Launch a video series dedicated to reviewing new gaming laptops and showing their performance
- A promotion that offers a gift card with a laptop purchase
- Website design to make your laptop categories more clear and visible on your homepage
- An improved comparison tool to make it easier to compare laptops
- Relevant niche product information for each category: gaming performance for popular games (gaming category) and battery life based on typical work scenarios (business category)
Now that you have these ideas, you can start ‘testing’ your hypothesis to see which ones are valid – so you can do more of what works, and stop doing the rest.
The 7 steps of Proactive Analytics
Proactive Analytics includes a 7-step framework. It takes the guesswork out of what to do at each stage of your campaign planning and execution.
- Define a business objective (keep the goal the same when you test your campaigns sequentially). This objective should be attainable and measurable.
- Brainstorm around what campaigns could achieve this objective. Don’t try to hit a home run with every idea; be courageous and experiment. Some ideas may seem wacky but could turn out to be precisely what brings unprecedented growth.
- Choose a campaign that has the most buy-in from the team members and the largest estimated impact. Don’t be afraid to try new things.
- Plan the implementation. It can be an engineering, design, or marketing effort, depending on the campaign’s nature. We suggest using the agile sprint methodology, where you set a fixed time frame for the development, usually one or two weeks.
- Implement your campaign and then launch it on time. Always make sure to involve those who will be doing the actual work during the planning stage. That way, you will get an accurate estimate of how long it will take to implement. Choose a realistic timeline.
- Measure your campaign results in a set period of time, depending on your industry and product. You can let your digital strategist help you decide on this number, but one month is a good rule-of-thumb.
- Learn if the campaign impacted your business objective. Remember, a campaign can impact a goal positively, negatively, or neutrally. It’s vital that you use a tool that can get you the most accurate answer possible. If you don’t have a statistician in your company, Mixpanel is such a tool.
We’ll be publishing an article to show how Mixpanel can be helpful in your Proactive Analytics strategy. Stay tuned!
Consider appointing or hiring a digital strategist
If you struggle to come up with campaign ideas, consider appointing a digital strategist within your organization. If you don’t have anyone who would be a good fit for this role and don’t want to hire someone, you are welcome to reach out to us. We’d be happy to offer a digital strategy consulting service and digital strategist training for members of your team.
We would advise that you don’t choose one of your marketers as your Digital Strategist and avoid letting the role focus solely on marketing. Your Proactive Analytics campaigns should sit at the intersection of your marketing, product, and content strategies. This is to ensure that you’re bringing about actual innovation rather than getting stuck just designing new advertising campaigns.
And remember, testing requires discipline. It’s vital to keep your experiment controlled, to avoid inaccurate conclusions. We suggest that you focus on one major campaign at a time. It may sound too little, but it is better to run tests more frequently than to run many simultaneously.