The phrase 'big data' gets thrown around a lot these days in tech circles, and with good reason. By analyzing big data (more specifically user data) you can discover patterns, tendencies, and insights. Once you harness your data, you can use it to identify new opportunities which can lead to smarter/faster business moves and ultimately happier customers. 

Big data is an aggregation smaller datasets throughout an industry. It helps businesses, governments, and individuals see what’s happening on a macro scale as opposed to a micro scale.

While the concept of big data might be exciting to data scientists, sadly, for most marketing experts it falls into the same type of category as financial accounting (mind numbing and boring). I have to admit that I was mostly in the camp of the latter group - Obviously I knew data was important, I just wasn't aware of 'how' to look at it beyond basic analytics. 

Like most opportunities that come your way, it's not always the primary objective that becomes the catalyst for success. I've worked on a couple of big deals over the years that I thought would be the 'next big thing' that would propel my business to the next level, whether it be financial gain or prestige. 

In 2017 Builder Designs was selected as the vendor to develop a commercial real estate application for a public company. This was a high six figure deal that was very prestigious but also had lots of strings attached. For example, it had to be complete in eight months or there was a 250k penalty. It was a rebuild of a 12 year old application, so there was a lot of legacy 'back doors' that weren't known or understood until we got into the design/build. Nevertheless, we were confident that this was going to be a huge payday for the company and we were thrilled that we got the contract. What we found out later is that our bid was 300k less than the next cheapest bid. That was a big red flag, but we were already committed.

The good news is that we completed the project on time. The bad news is we didn't make any money - the exact amount we lost on the deal I try not to think about. But the experience we gained from that build out was really two fold. First, we got to work with a lot of top level software developers and saw how complex applications are developed in a controlled environment and two, we saw how data scientists work when they review big data. 

When a large public firm gets ready to rebuild an application that has a direct impact on their user base, they spend a lot of time and money to make sure that the new app has the functionality built in from the ground up. They use data to drive that process. This specific application was generating a huge amount of user data and the data team that we worked with had a unique process where they would model data and then prototype user interfaces around the desired goal. Making the app easy to use drives adoption, which was a key factor in their success metric. 

So then the question is, how does big data apply to home builder web? How can we effectively use data to create and empower the home builder website to deliver an even better user experience? 

The first step is getting your eyes on as much data as you can. Builder Designs has more than 400 home builders on our platform which drive approximately 17M unique visitors per year to those sites. We rolled all of the builder analytics into one macro snapshot and looked at the basics: percentage of mobile versus desktop traffic, time on site, bounce, conversion, etc. We then compared current data to last years to look at trends. 

Next, we took the top 25 builders we work with and compared their data to the macro to analyze the differences. What we found is interesting and in some ways the opposite of what we expected to see. For example, organic desktop traffic is still the highest converter and evidence shows that trend is actually moving away from mobile when it comes to form conversions. We also learned that people will do just about anything to avoid filling out a contact form. 

When analyzed conversion data, we were able to see which sites have the highest conversion percentage. We can further isolate which product interfaces (plans, inventory, communities) have the best conversion data. The higher the price point, we see that people look at plans before anything else.

Big data enables us to stop guessing about website performance. We now have the ability to pinpoint user behavior and fine tune user experiences for your prospective buyers.

We believe that the builder who can create the most informative, curated, customized experience for their customer, based in data, will put themselves in a position to succeed. We also believe in transparency, so we've assembled some of the data we compiled in our work for you to review. If you'd like to get on a call to dive deeper into this discussion, just let me know.

Chip