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The term “big data” has been captivating us for nearly twenty years. While the amount of data today’s companies store and track is definitely big, the truth is, most of it has little (if any) value. Don’t get me wrong, I am a strong believer in using data to drive change, but I think it’s important to understand how to determine what data is actually worth using.

Over the past year, I’ve spent my “free time” earning a Master Certification in Business Intelligence. I say this not to brag, but to show that I am committed to the field of data science and analysis. Many get sucked into the belief that “more is better”, this often leads to analysis paralysis. In the video below I walk through the big data lie and how you can find the data that matters.

Video Transcript:

Hey if this is your first time watching, or maybe you’ve been watching a while and haven’t yet hit subscribe, please do, we would love to have you join our community. So over the last fifteen years or so, the term “big data” has been extremely important. It’s actually more like 20, 25 years. As companies have generated more and more data points, they’ve been storing those data points and now they’re trying to figure out what to do with all that data. Now what has really happened as a result of this is we’re drowning in data. We have so much data that we really don’t know what to do with all of it and the reality is most of the data we have is duplicated or it’s incorrect data, but we still are obsessed with “big data” because we could use data to do some really cool things, like teach machines how to use that data to identify trends and spit out awesome numbers and help us really do our jobs better. That’s what machine learning and AI is all about.

It’s about feeding machines data, giving them a script to work off of. Then they can use that script that they’re learning in order to give us smarter answers. But what happens for most business is we start to store all of this data, but we don’t really know what to do with it and we just start trying to pull data points out and really it’s not helping us make smarter decisions, it’s just helping us put data next to why we did what we did and validate ourselves even if it’s not validating the right answers. So if you watch the intro I said, “Big data sucks.” And the reality is most times it does. Big data is very hard to work within this whole business intelligence stream, business analytic stream of a business it can get very, very confusing. So how do we use data effectively? That’s the real question. So that’s what we’re going to talk about today. So you’ve maybe heard something before called a KPI. Now a KPI stands for key performance indicators.

Now the reality is most business when they look at performance metrics and that sort of thing, they don’t really define KPI’s. What they typically do is they go to their database and they just start pulling out metrics and when you do that it’s very dangerous because there’s so much to choose from. You can get analysis paralysis or you can just start putting stuff on there that really aren’t key performance indicators. Now the key to KPI’s is this letter here, “K”. Key. Key means goal oriented or attached to the business goal. So anything that is attached to the overall business goal of that business unit, the business itself. Those are going to be metrics you want to track and those are metrics that are going to be key. Now when you’re doing this, you only want five to seven, maximum seven. Honestly, I would really push more towards the five number because that’s going to allow you to keep your goals more focused. We talk a lot about smart goals in marketing and sales, but you can’t have a smart goal if you don’t have a benchmark.

So what these key performance indicators are going help you do is at least get that benchmark. Allow you to start working towards what you want to see and then you can benchmark against that and then you can actually create smart goals. Now some tips for creating KPI’s. They need to be attached to the goal. So if your goal is more revenue, the KPI’s need to be attached to revenue. If your goal is more revenue, the KPI’s need to be attached to revenue. If your goal is more visibility, the KPI’s need to be attached to visibility. If your goals better production, then your KPI’s need to be attached to the production process. As you can see, they need to be attached sequentially; they need to be attached to your main goal. Sometimes you can’t find the right words. So when you’re defining your KPI’s you want to look for those things that matter the most. If you’re a marketing agency and your main KPI is lead generation, you want to make sure that all of your KPI’s are attached to lead generation.

So one of those things that may be a factor in leads may be sessions. So you might want to track marketing. Are you generating the right amount of sessions for the right amount of marketing channels; organic, direct, social, off-line events. Other things you might want to track are contacts, leads, people coming in your site who’s giving you information. Then we also might want to look at the quality of those leads. So are these leads staying at a low level, maybe just subscriber, or lead level. Are they moving towards the funnel of becoming a marketing qualified lead and a sales qualifying lead. So those are some of the things that you want to start with. One of the things that Stephen Colbert talks about is beginning with the end in mind. You want to kind of think of this like a race, where you’ve got a finish line and the finish line is your goal. Before you ever go into your database to start trying to pull out number, you want to understand what you want to do. Again it’s attaching back to this KPI.

Once you have the goal, now you want to reverse engineer the process to get to the data points that matter most. Most of the time you’re going to dig into your database and you’re going to look for numbers that look cool, trends that look cool, but if they don’t attach to your goals, they’re just vanity metrics. They really don’t have a purpose. The point is, you want to find those tiny bits of data that are going to allow you to make the most impact. Sessions may not be the biggest thing that you’re tracking as a business, but if sessions play a big role in lead generation which plays a big role in revenue generation, then that’s a key performance indicator and that’s a goal that you’re trying to achieve, sessions becomes a little bit more important and you want to pull that out. So not every piece of data that you’ve been tracking matters. You can have this huge ocean of data that matters. A lot of times people talk about the iceberg. Then you see the top data, then underneath you know you’ve got all this under here.

The reality is most of this data under here, under the water, maybe this much of it’s worth it, over here. The rest of it’s just junk most of the time. It’s either like I said before, it’s duplicate data, or it’s improperly processed data. It’s data that just really doesn’t matter much to the goals. The real goal in getting something out of your data is diving down into the water and chipping off this chunk that actually matters, bringing it up to the surface and attaching that to key performance indicators which is going to allow you to reach your goals. So I hope you got some important insights today. Dig into your data, but find the points of data that matter. “Big data” on its own, it sucks. It’s really complicated. There’s a lot going on and if you don’t really have an idea of how to extract all that data, or really cleanse that data or make that data more qualified.

You can get really overwhelmed and bogged down in the numbers and then you’re stuck, but if you can allow yourself to go beneath the surface, find those little bits of data that actually matter, that are tied to your goals and your KPI’s. You’re going to be able to make a big difference in your business and make sure that you’re getting your goals. If you have any questions, please comment below. We would love to contact you and talk a little bit more about this. I love this subject. I’m a little bit of a nerd when it comes to the “big data”. So we would love to continue just to build that relationship here. If you’ve got any questions, please comment below. We’d love to continue the conversation until next time. Happy Marketing.