Make your eCommerce data driven
There are three steps between online good luck sales and data-driven e-commerce. Every step is one forward, towards more conversion. Incentro helps you during this trip.
Step 1: know your visitor
Maybe your site is a sweet invasion, a coming and going of various figures. Or do the same visitors always target specific information? Anyway: data is knowledge, and knowledge is power. Certainly within e-commerce. The better you know who will do what for you (and why), the more successful your next step will be. We start with three basic questions. You probably already know this, but for the sake of completeness, let's start from the beginning.
__ Who will be on your site? __ What do you actually know about your visitors? How old are they on average? Especially men, more women or both equally? Are they a bit technical or not? This type of profile information can be retrieved on the basis of account information. Very important, because with this you get a better picture of your audience. Maybe you think that other visitors will come to your site than is actually the case, and you completely miss the mark.
__How do they end up there? __ Access is a condition for conversion. In other words: to do or buy something on your website at all, they first have to end up there. You will therefore need to know how customers end up on your site, for example organic, paid or based on "referral". This information is also crucial because it tells you what is the best way to invest. Consider an extra AdWords budget or you can profile yourself more actively on social media.
__ And what exactly do they do there? __ Ok, people have found your site and you know who they are. Then you are probably curious what they are up to. Which routes do they take, how long do they stay and how well do they convert?
You can easily retrieve this data with the standard version of Google Analytics. But for step 2 you soon need more detailed customer information. And then you can no longer manage this. Incentro tells you exactly how you can access that information.
You can do this with step 1
- Get to know your visitors and respond with the right content
- Find out how you can get more customers on your website
- more efficient use of your Adwords budget (bet on the best channel)
- Which keywords attract the most visitors or convert best?
- Which content provides extra traffic?
- Do you have to invest more energy in (for example) blogs and video?
- Adjust the customer journey - at which step do many customers now drop out?
- Optimize retargeting - for example through personalized mail campaigns
- Benchmarking - perhaps you are already doing well, compared to the market average
Step 2: map the (conversion) process
You now know who your customers are, where they come from and what they do on your website. Valuable information, because you can use this to find out which customer journey converting customers go through. As said: this is not possible with Google Analytics.
__Full basket, don't buy anything: why do people drop out? __ Someone is doing something in his shopping basket. Nice, on the checkout. Only: because your payment environment is unclear, or there are high thresholds in the checkout process (log in first, for example), they stop. Deadly sin of course. Once it is clear at which step customers leave your website, you can make the check out more logical, smoother and more efficient.
Higher order value The orders come in, super! Now it is important to increase the average value per order. This can be done by selling related products, such as a matching shirt with a particular pair of pants or sunglasses with a bathing suit. With this you help the visitor. Really, it can make a huge difference.
__CLV: what do your customers actually deliver? __ Then it is important to see what happens after the conversion, for example when it comes to customer service and returns. A product that generates a lot of sales seems nice. But it becomes a different story if it turns out that you have to incur high costs. Knowing what a customer is really worth is also called "Customer Lifetime Value" (CLV). Very valuable!
At this step it is crucial that you combine different information sources into one data layer. This enables you to look over the processes, at the larger picture, so that you can calculate the CLV. This is really specialist work, Incentro tells you exactly how you can access that information and can also do this for you.
You can do this with step 2
- Optimize your conversion process (less dropout during the purchase)
- Optimize your post-conversion process (fewer returns thanks to prior information)
- Product recommendations specific to the visitor (increase order value)
Step 3: predict customer behavior and convert faster
Okay, you know your customer, you know which route he takes on your site and how conversion takes place. Super useful, but now it becomes really interesting. With this knowledge you can proactively help customers. For example via a chatbot that helps your visitors with the right questions. Do you want to know more about this product? Or do you need help from customer service? Keep in mind: Google Analytics was no longer sufficient in step 2, here you should really start thinking about applications in the field of big data and machine learning.
You can do this with step 3
- Identify and persuade high potentials with customized content
- Help customers in an automated way with what they are looking for, and relieve your customer service
- Predicting the CLV: how much do you want to invest in certain customers?
- See where someone is in the customer journey, and offer (more) relevant content there