We live in an age where we can get data on nearly anything. Businesses pay handsomely to use this data to serve ads to the right people, yet often downplay the role of statistics in business decision making.
This happens especially with regards to using website analytics. Rather than using this rich source of data for things like product development, many rely on old-school methods like intuition and leadership instead.
Website analytics provide low-cost (and sometimes even free) data about the people who buy your products, as well as data about people who don't become customers, which is equally important.
Businesses can, and I believe should, rely more on their website analytics to help dictate product development choices.
Read on to learn how your business can gain valuable insights and develop products using this cheap and unbiased data source.
How Businesses Typically Develop Products
Businesses create product offerings in any number of ways, and they're each unique to that business.
Some product decisions come from the top of the organization; others have product teams that might work with multiple departments to figure out what products to make next.
Yet one thing I've noticed that most companies don't do is this: consult their site analytics. I would argue that this is a grave mistake, as there's not many other sources of data available that are as unbiased and truthful about potential customers as website analytics.
Rethinking the Role of Statistics in Business Decision Making
There is a treasure trove of product-shaping data just waiting under the hood of your site analytics program. Consider the prospective customer who lands on your website.
This is a data point of watching somebody go through the process of deciding whether or not to purchase your product. It's not what they said about the experience in a survey—sometimes people aren't truthful—but what the visitor actually did. This is data on what the customer actually did on your website, not what they said they did.
If you think creatively about the data you have and how people navigate your website, you can start to see patterns. Then you can get inside your customer's head and use this data to start answering questions like:
- Why didn't they buy our product?
- Why did they leave our website so soon?
- What are people searching for that we don't offer?
When you can start to draw insights for these questions (and others) from site analytics, you can start to understand how to improve your business's offering.
But a word of caution: implementing this in a business is easier said than done. Being able to let go of ego and trust the data in the decision-making process is crucial from your leadership. If your company can't do this, it may be hard to put any statistical insight into practice.
How to Implement
Implementing a strategy for trusting site statistics in business decision making isn't really that technically involved. Most websites have some sort of analytics or tracking already installed, so the hard work comes from interpreting and drawing insights from the data.
You probably already know a fair amount of data about this person once they land on your website, using data like what site they were on previously, what search terms they used to find you, whether they came from an ad or email or Twitter, and so on.
This is especially helpful for product development when you have data on people who didn't purchase your product or service.
Step 1. Install and/or become very familiar with your tracking software.
Google Analytics is probably the most popular website statistics service, but Clicky, Piwik, Chartbeat, SE Ranking and a host of others out there will typically provide the baseline of what we need to learn about our customers. A quick search can help you with your specific software installation. Once installed, here are the things that you'll need to know and pay attention to.
Which pages do the most people leave your site on (ie. high bounce rate)?
High bounce rate is a good indicator that the page isn't providing what the customer needed to make the sale.
Which pages do people spend the least amount of time on?
Another good indicator that your product or marketing didn't live up to expectations.
What sources provide the most sales? The least?
Knowing what works is important, especially when you frame it within the context of where they came from.
What search terms brought them to your site that had a high bounce rate?
I'll give an example of why this is important. One of my client's most popular search terms to their website was for their mobile app, which they hadn't built yet.
The company was on the fence about spending the resources to build a mobile app, and the searches proved that there was a high demand for it. What are people looking for that you're not yet providing?
What are the paths of both successful and unsuccessful conversions?
How are people moving about your site when they purchase an item?
Most analytics programs give you the snapshot of how visitors interact with your website. For example, do many people land on the homepage, click a link to the product and then buy from there? Or do they meander more around the site before making a purchasing decision?
You can utilize a lot more data to support the role of statistics in business decision making, but understanding these core metrics above can give you a firm grasp on what customers are actually doing on your website.
Step 2: Synthesize the data
This process achieves two things at the same time. First, it gives you very concrete data on where and how to fix your site by identifying pages that aren't meeting customer expectations. By identifying pages with high bounce rates and other negative factors you can start to shore up those lackluster pages with better content and marketing.
More importantly, you'll also start to see where your company isn't meeting demand with your products or marketing. If people are already looking for a product that you don't yet carry or make, you have data that suggests that there is demand for it. If people are leaving your site quickly once they land on a product page, the page or product might need some refining. Overarching problems become evident, as do successes. It's all important data.
Web analytics certainly aren't the only factor in the role of statistics in business decision making, but they add powerful insights for dictating product decisions. Don't ignore the cheap and reliable data available to you.
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