It seems like you cant go anywhere today without hearing about the importance of big data. But eCommerce companies especially know the importance of the data revolution, simply because of how much of it is available to them.
In a certain sense, the fact that all eCommerce companies now collect tons of data actually makes it both more and less important to them. More important because without it they are sure to fall behind the competition; less important because collecting data alone is no longer enough. The real money is now made in how eCommerce companies put their data to use. And its precisely because e-commerce stores generate so much data that its essential for them to use the right methodologies and select the right analytics tools if they want to have any success using it. Bottom line, if your business isnt using the data you collect to maximum effect, you wont get you a competitive advantage at all.
Yet despite the fact that this isnt exactly a secret, many eCommerce companies continue to be unable to see the forest through the trees.
How Do You Use Customer Data Intelligently?
Of course, that can be easier said than done. For starters, it can be a challenge to decide on what you are even want to collect in the first place. The nature of the web means that there are tons of different data points that an eCommerce company can choose from, including customer traffic, the lifetime value of customers, customer conversion rate, and more. Deciding what the most important things to measure from amongst these is already a daunting enough challenge in and of itself. Add figuring out the best way to piece everything you measure together on top, and it just makes the task even more challenging.
However, if you are feeling paralyzed by all of the possibilities, there are ways that you can break through. If your business is currently struggling to make the most out of the data it collects, here are two simple strategies that can help to get you pointed in the right direction.
- Dont be intimidated about getting granular
It starts with a change in mindset. You should first take a step back and embrace the opportunities that the data your eCommerce business collects offers. Its a huge mistake to view the ability to collect extremely precise, multichannel data as a problem rather than an opportunity.
Looking at it as a burden might cause you to ask broader questions that you feel can be more easily answered, rather than precise questions that require a thorough analysis of different data points. Doing that will cause you to overlook the possibility to seek answers to extremely granular questions. Once you start down that road, you are simply leaving money on the table.
For example, why would you settle for finding the best price for a product category when you could drill down to the product level itself? Dont fall into this trap. Think critically about what the true questions you want your data to answer are – and dont be afraid to dig deep.
- Simplify KPIs to get to whats essential
Once youve figured out the questions that you want to ask, the next step is figuring out how to get the answers.
The big data revolution started with companies seeking to collect as much data as they could as quickly as they could. But companies have now realized that their blind zeal to collect as much as possible as quickly as possible only resulted in them drowning in a sea of useless information.
That initial fever has now given way to a more deliberate approach. Smart eCommerce businesses have realized the need to refocus their strategies towards fewer but more effective KPIs.
You should be doing the same. When considering what data you need to collect to answer the questions you have about your customers behavior, think about the two or three most essential things to measure – and dont get bogged down with the rest.
Selecting the Right Tools to Measure Customer Data
E-commerce businesses thrive on technology, and so they also understand that it is technology which powers the big data revolution. The ability to get down into the nitty gritty of the most specific questions wouldnt be possible without the technology that powers it.
And its precisely because the breadth and depth of the data produced today could only be achieved by technology that the same holds true for what is required to effectively analyze it.
Drawing the proper conclusions about your eCommerce company’s data requires you to invest in the right business software to do so. Today, the tools available are as varied and specific as the data they analyze. What you need will depend both on the type of eCommerce company you have, and the challenges that it faces.
For example, eCommerce companies looking to create seamless customer experiences and seamless multichannel sales might consider a point of sale system (POS) such as Vend that uses data it collects about customers to suggest targeted sales promotions.
Or, if you are an eCommerce company with a high rate of shopping cart abandonment online, you can implement software such as TellApart that can use data to identify visitors likely to abandon their cart – and then offer them targeted discounts to induce a sale instead.
If you have correctly identified the specific problem you want your businesss big data to solve, all you need to do is fight the right software tool for the job. Really, the possibilities for targeted strategic action are only limited by your imagination.
How to Get the Most Out of Your eCommerce Companys Big Data
Ultimately, the possibilities that big data opens up for eCommerce are huge. Never before have you been able to get such detailed insight into your business operations, and tailor your strategies accordingly. And although the opportunities this creates can be overwhelming at first, businesses that can get the right answers to the right questions will come out on top.
Fortunately, there are tons of tools to help you do this. Just commit to shifting your approach from collecting big data to using the right software to generate smart data and youll be well on your way to reaching your future profit and growth targets.
