3 Ways That Data Improves Product Development And Deployment

Data has implemented itself into almost every area of internal business, shaping communications and PR to sales strategies and leadership. But what about product development? Unsurprisingly, considering that data-driven choices are three times more likely to succeed, product development and deployment is also a field that is set to experience major benefits from listening to the data.

By collecting data, both on interaction and product satisfaction, the product development team can use insights from their customers to create a better understanding of not just how a product is being used, but why it’s being used. From there, by focusing on refining what’s being ignored and bolstering what’s already successful, product teams are able to craft much higher-quality services.

In this article, we’ll be taking a look at three ways that data improves product development, demonstrating exactly why your business should be turning to data analysis at every opportunity.

Complete Understanding of the Customer

At the end of the day, no matter if you’re creating software to sell as a service to customers or are crafting a physical device, you’re going to be creating for a certain audience. Both B2B and B2C companies have something in common – the fact that there will always be a target market for their products.

While general ideas of who might be the ‘ideal customer’ can be built up by looking at what solution your product or platform solves, this lacks complete accuracy. One of the best ways to understand who exactly is buying your products is to look at the customer data. Data is an invaluable location for farming demographic information.

By collecting information about exactly who is buying your products, you’re then able to focus on developing additional elements that will further the utility of your product for that particular user segment. By focusing on developing the product in line with those that are buying the product itself, you’re able to create a hierarchy of implementations that need to be made, instantly working out which changes to make first and how best to develop your product.

Equally, by knowing exactly who your customers are, you’re then able to more effectively market your product. Within each campaign, you can focus on the product features that are most useful to your target demographic, helping your product to shine.

Understanding your customers does more than just help you further shape the products that you offer, it also directly feeds into improving retention rates, boosting sales, and ensuring your customer satisfaction rates remain as high as possible.

A/B Testing

Customer data is a treasure trove, quite literally guiding you toward plotting a course to continually improve how effective your product is. When you have a product, there are several different ways that you can take your development strategy. While each of these may have different benefits, there’s no real way to tell if one choice is better than another. That is, until you get access to the data behind these choices.

A/B testing is the process of offering certain percentages of your customer base distinct features. These can be slight variations of your platform, with interactions from each divided segment then generating information about which variation is more useful or successful for users.

A/B testing is something that can be run continually, with slight variations being made on a continual basis to constantly increase the utility of your product and the satisfaction that customers have with your platforms.

A famous example of effective A/B product testing is from Google, when they ran a shades of blue experiment. Within this experiment, a small segment (around 1% of users) were shown a different shade of blue on their sales buttons. By testing out over 40 shades of blue across their audience, they found that one shade was significantly more clicked on than others.

By then changing their buttons to this shade of blue, Google increased their profit from these buttons by over $200 million. Just from one simple change, Google triggered a massive result, demonstrating the true power of A/B testing, even on a minute scale.

Running A/B testing on every single aspect of your platform can help you to continually improve your product, leading to higher retention rates, satisfied customers, and a higher profit over time.

How easy is A/B testing?

Part of what makes A/B testing an effective product creation strategy is that it is incredibly easy to set up and run. If you have a service, all you need to do is split your userbase into segments, then deliver different segments a slight variation of a feature. Over time, you’ll be able to collect interaction data from each of these segments to build up a better picture.

The main difficulty in the past with A/B testing is that it produces so much data from the various simultaneous segments that it was once fairly difficult to keep track of. Especially when that data pertained to different departments, data silos would frequently occur that obfuscated any results.

However, with the vast availability of cloud data warehouse services, this is now a problem of the past. By supplying a centralized location where all relevant results from the A/B testing can be stored, anyone can then collect the data and run analysis with ease. Due to the advancements of data tools like these, there is now virtually nothing holding businesses back from utilizing A/B testing.

This can be seen to a great extent with service companies like Netflix, which runs A/B testing on practically every element of their site, homepages, sign-up portals, and copy.

Track the Customer Journey

When selling a particular piece of software or a platform that users continually come back to, you’re able to gain a wealth of usage data, displaying information about how often certain features are used, if tutorials are followed, and the frequency with which users perform certain actions. By collecting this data, you’re able to build up an effective depiction of your whole customer journey once they start using your products.

By tracking the customer journey, you’re able to see exactly where your platform is used well, and precisely where people become confused and have difficulty with it. If you notice that one major function is considerably less utilized than another function, you can follow the user journey to see where people are clicking off that function.

By then creating bridges that help move through the location where many previous customers stopped, you’re able to continually refine that function of your product. With this, you’re able to use customer data to make your product better over time, creating a holistic system that benefits your customers and your sales figures.

Final Thoughts

Product development and deployment is essentially a game of trial and error. While you can have pre-product testers in almost any industry, nothing compares to harvesting user data once your product is actively deployed. With this data, you’re able to make data-driven decisions that move your product toward a continual period of improvement.

From using A/B testing to refine certain features to harvesting customer information to create better products for your user base, there are a range of ways that data enters into this industry. As you begin to use data to make informed decisions during the product creation and deployment cycles, you’ll create more effective services and always keep your customers as satisfied as possible.