Driving Safely with your Data
Be data-driven. Your clients have heard it time and time again. But guess what? The road to driving with their data is strewn with potholes that can take them into the weeds. How can you help them be data-driven, safely and efficiently? You’ll want to avoid these common mistakes that can ruin the trip and have your clients wasting time and money chasing down a side road to an unknown destination.
So how can you help the businesses that rely on you to handle their data, avoid the potholes, and complete their journey to data-driven marketing safely? Here’s our guide on Safely Driving with your Data.
1 Clean the Data
So guys – it all starts with quality data. We’re talking pristine. Why? Because getting your data in the absolute best shape it can possibly be in will determine how the rest of the journey goes. Period. Not getting your existing data in the right shape is like putting the wrong information into your GPS navigator. You just won’t get to where you want to go. Start your data-driven journey by making sure the data you’re using is clean. If it stinks, whatever you do with it will stink too. Cleaning, hygiene, un-stinkifying, or polishing – whatever you want to call it – just make sure your data is up-to-date, accurate, and standardized. Here are the potholes on the road to clean data and how to avoid them to keep on the easy street to data-driven marketing.
The Pothole – Dirty, silo’d data
This pothole is filled with dirty, out-of-date data that’s in incompatible silos.
This one can catch you before you start. It may seem like it’s not that important, but cleaning your data isn’t optional. If you bypass this step, it is like heading out on a trip following the wrong map.
Out of Date Data
The best data cleaning can’t help you if you’re working with old data that’s no longer relevant. Remove or update old customer information for smooth driving. Seriously. Get it outta there!
Incompatible Data Silos
One of the biggest obstacles to cleaning your data is getting it all in one place. If you have multiple sources of data in silos that are incompatible with each other, the task of consolidating, merging, and removing duplicates is just that much more difficult.
Manually cleaning your data has all of the inherent problems caused by manual entry of your data. Things can get missed, and more mistakes can happen, especially when dealing with enormous data sets. Nobody wants to do it anyways, especially when technology can do it so much better.
Stopping at just data cleaning
While cleaning is the first step, and an important one, it’s not the only step. You may have accurate, complete data, but it’s just data – not actionable insights. Keep going!
Avoiding the Potholes in Data Cleaning
One way to avoid all of these potholes is to use a high-quality data cleaning service, that’s automated to avoid human error and leverage the superpowers of artificial intelligence and machine learning. Make sure that whatever solution you’re using can:
- Bring information in from all of your client’s data silos and consolidate them in one place.
- Detect and correct out-of-date information.
- Standardize formatting on all types of customer contact information (for example, addresses and phone numbers)
- Accurately match and merge duplicate customer records.
Now you can continue the journey to data enrichment refreshed and ready to rumble.
2 Enrich the Data
The next step along the journey? Enrichment! The goal here is to add as many different pieces of information as you can, so you have as complete a picture as possible of your client’s customers. This step is important because what you don’t know about their customers may be the very thing that your client needs to attract and retain them. If you do this part right, your data will be more accurate and complete and will yield better models and results for the next part of the journey: analyzing. But we’ll get to that in a bit. First, let’s talk about what to avoid when it comes to data enhancing.
The Pothole – Not enough, mismatched data
This pothole has data that’s mismatched or not enriched.
If a customer record is matched up with information for another person, or you’re not matching when you should have, you’re in trouble. Faulty data means the picture of your customers is incomplete or wrong, which means anything that happens with that data could also be wrong. Which means, down the road, your modeling is going to be off. And that’s gonna suck in the end. (By the way – if you stick around, we’ll eventually show you just how all of this data cleaning and modeling stuff found some serious gold for T-Mobile. Oh what??)
Not enough enrichment
When it comes to data modeling, you can never enrich your data too much. Every additional piece of information for a customer paints a clearer picture of who your customer is, and increases the accuracy and predictive ability of your model.
Avoiding the Potholes in Data Enrichment
The key to avoiding these potholes is making sure you’re matching the data you have accurately and fully with the enrichment data. The last thing you want is to go through the process of data enrichment and come out with your records filled with more inaccurate data, or great data that was missed.
So, make sure you are using data enrichment tools that:
- Have tons of information available for data enrichment
- Can reliably and fully match your client’s data with your enrichment data
3 Analyze the Data
Now you’ve arrived at the home stretch, where all of your work up until this point pays off. You want to pull actionable insights from your client’s data – meaning, you want to be able to actually do meaningful things with your data, and be able to measure the results. If your clients see the results of being truly data-driven, they’ll keep coming back, they’ll refer their friends, and you’ll have to buy a bus. Here’s how to make your data analysis ride a smooth one.
The Pothole – Expensive, rudimentary modeling
This pothole is all about spending too much money for less-than-stellar results.
Trusting your gut
For years, trusting their gut was all marketers had. If you have a lot of experience and your intuition is good, it can mostly work, most of the time. With today’s tools, though, you can do way better.
Expensive Data Scientists
Hiring a data scientist or a team for that matter can be extremely costly, and in the end, could delay or derail your efforts. We hate to break it to you, but most data scientists spend only 20 percent of their time on actual data analysis and 80 percent of their time finding, cleaning, and reorganizing huge amounts of data, which is an inefficient data strategy (InfoWorld). So you could easily find yourself a year down the road with not much to show for it besides an extremely high bill.
Manual and/or rules-based modeling
Even if your data scientist team is the best in the world, rules-based modeling just can’t compete with the speed and predictive power of AI/Machine learning. Period.
Mismatched or missing data
Analyzing customer data where some of the records aren’t complete, or contain different levels and types of information, you’re likely to end up lost and not sure what to think.
Avoiding the Potholes in Data Analysis
Avoiding these analysis potholes comes down to preparing the data well, and then using all of the power of a great predictive modeling tool to make the most of that clean, rich data. The right predictive modeling tool can deal with far more complexity than even the most advanced, most highly-trained, and most experienced human brain. Use tools that:
- Leverage computing power, artificial intelligence, and machine learning.
- Are backed and developed by data scientists to be better than them.
You can use these tools to confirm (or refine, or reverse) what your gut is telling you, or use them instead of your gut — just use them.
Enjoy the Rewards of a Higher ROI
Your reward at the end of this truly smooth, data-driven journey: accurate, actionable insights that help your clients get the results they need to do business better. Whether they’re measuring ROI, CTR, CPC, or Conversion Rate, they’ll see significant improvements from hiring you to get them data-driven. And when your clients do well, you do well.
Be safely data-driven with Versium
Versium’s got all the solutions you need to drive safely with your client’s data and avoid the potholes. And we mean all of them.