Big Confusion Around Big Data

So here comes that term again, "big data."

You can't escape it. By now you've heard it mentioned at countless conferences. Analysts call you regularly to offer their services, and a board member just had dinner with a guy that says if you aren't using big data, then you are failing as an organization. So when will this stop?

It won't ever, really. Big data isn't just hype; it's an invaluable tool that can be deployed to generate real, actionable insights. Go figure, right?

So here's the situation. DMOs require a CRM system to efficiently process and analyze the explosion of information that is generated by the industry. The good news here is you are sitting on a gold mine of data in your CRM. The potential bad news? You may only be using it to measure performance. The true value in big data comes from highly profitable, data-driven decisions.

The real question isn't whether big data is valuable. Rather, it's how do we get from big data in our CRM, all the way over to actionable insights? To help connect these dots, we've provided a checklist for making sense of your data. Go in depth with each step below, or click here for a quick, condensed checklist for your viewing pleasure.

The DMO Guide to Data-Driven Decisions

Step 1) Clean Up Your Data

All that data is useless if it isn't based on facts and relevant information. Sadly, this is the part where most people quit. There is a lot of data from a lot of places pouring into your CRM, and trying to put some SOP's around it for good data is tough. But this is where the groundwork needs to live if you are going to move forward. Many of the processes you establish or update here will also make your organization more efficient and give you many insights just from the nature of it. This step can require a lot of time, so you may want to take use of third party services out there that can help with this, especially from the base level information surrounding contacts and companies.

Step 2) Identify Your Metrics

Many of you already have this part started due to your need to measure performance. The difference is looking for the common denominators that can create correlation and insights. Lets look at bookings for example: if we started to look at region, requested peak, previous bookings, site inspections, vicinity, market segment, season, attendee count, and source across all of your booked business, and created segmentation profiles, I'm pretty confident that it would make your prospects much easier to evaluate for the likelihood of winning the business.

Step 3) Keep It Objective

You just spent a lot of time scrubbing data and gathering data points and can finally start laying out the landscape. If the landscape starts to look bad, it's not unheard of to start trimming away some of the bushes to make it look prettier. This is ill advised. You need to accept what the data gods have given you. Verify and try new potential correlations to be sure, but don't exclude or ignore because you don't like what it is telling you. Don't let the short term goals distract you from the long term goals that will make the company more successful. This is a long process, so buckle in for the ride.

Step 4) Automate It

Lets take all that hard work and make it easily repeatable. Whether it is through technology such as Destination Dashboards or defined process, you want this to become a way of life, not a yearly act of busy work.

Step 5) Evaluate and Act

The results are in, now what do we do? Well it really depends what you are measuring. If we look at the most common form of big data, it's identifying your key demographic and how they consume your product. Once you have that, we can do all sorts of great things. Bridge the gap and forecast prospective consumers to set goals and performance metrics. Use this information to source your consumer and make a campaign around it. You've likely done this to some extent, which means you know what big data is and how to use it.

Step 6) The Next Level

We all use big data already, but sometimes we don't label it as that and are easily convinced that it is a magical unicorn far beyond our grasp. It really isn't, though, and rather the applications simply elude us. Lets go back to that consumer marketing campaign that you have all taken part in. How long should you run the campaign? Did you just get a budget for it and run it through based on cost? Did you simply limit it to a seasonal time block?

Well what if you took all the data from previous campaigns, put in place the methods to track success and economic impact, then evaluated all of that by using an optimal stopping model to determine what length of the campaign will net in the most profitable result? That is a powerful approach that lets you stand on your data for the decisions you made. You can take action with confidence that your process will yield the best results and take in the praise when it comes full circle.

Big Data Has Big Applications

There's tons of applications for big data once you start approaching it the right way. Removing the uncertainty of a gut instinct decision and backing it with real data that commands your actions makes your organization more dynamic and adaptable to the industry.