Personalized shopping has rightfully become one of the most frequently mentioned eCommerce trends of the past couple of years. The funny thing is that it’s not a new concept. Just like with almost any eCommerce craze, it simply had a different name. For example, David Meerman Scott talked about real-time personalization back in 2010, which is nearly a decade ago (yes, time does fly). Why is it such a hot topic right now, then?
It all makes sense. A significant portion of online businesses have dozens if not hundreds of competitors selling the same products. In this endlessly competitive space, each of such businesses is looking to partner with an eCommerce development company to connect with customers through technology. Of course, companies are not in it for emotional connection with the customer (at least most of them are not). They’re here for profit, and personalization offers incredible ROI if executed properly.
Additionally, the mobile revolution and the emergence of big data make it all possible. Businesses stack so much data about their customers that it’s impossible to ignore it. With the sophistication of modern analytical tools, eCommerce businesses can truly start personalizing online experience for their clients as if one to one. But not a lot of them do. Even if they do, not many of them truly exploit the various facets and techniques of personalization that drive sales and conversions. Let’s take a look at some of the steps and strategies that eCommerce stores can exploit to personalize shopping for their visitors.
Build a Personalization Strategy
Today, your eCommerce business has to be prepared to stand out. Personalization is a driver of growth and a separate marketing domain in itself that requires a different approach. A personalization strategy allows you to answer a few simple questions: What? Where? When? But before you start building it, there are three more questions that you have to answer.
Why do you need the strategy in the first place? Because it allows you to prepare your business for a personalized shopping experience that your shoppers will demand from you. It incorporates technical aspects of gathering, analyzing, processing and exploring customer data in a way that’s specifically geared towards personalized marketing, with its own rules and requirements. Sounds complex? That’s because it is. You have to treat personalization just like you’d treat any other marketing activity – as a potential ROI driver.
The format of this article doesn’t allow us to build out the thoughts and ideas about effective personalization strategies. But there are some fantastic guides and exploratory articles out there that can help you anchor your starting point for a personalization strategy:
Employ Advanced Segmentation
There’s nothing particularly unique about this approach to personalization. The only difference between advanced segmentation and your usual segmentation is the granularity of data that you’re willing to use as a marketing segment.
For example, you might have people who purchased a t-shirt from you last year but didn’t buy anything same time this year. This approach seems like a straightforward way to segment. But what if you added specific information? What if you segment by holidays? For example, a segment that includes people who purchased during last year’s Thanksgiving, but didn’t come back to the store this holiday season.
This kind of segmentation allows you to create laser-focused promotions. This tactic is a step above your usual segmentation by gender and location and allows you to create more targeted promotions, achieving narrower segments overall. These divisions are called opportunistic segments, and although they’ll not be the bulk of users responsible for sales, they do create additional opportunities for segmentation which results in a more personalized experience for each member of the segment.
This is not your ordinary ‘Since you bought A, you might be interested in B’ type of recommendation. We’re talking about personalized recommendations based on data from other users, which you’re accumulating. It requires a more technical implementation, but the reward could be huge. Amazon generates 35% of its revenue via recommended products. But how?
Data source: ibm.com
Enter recommendation engines – sophisticated algorithms that calculate the most likely product that’s going to be interesting to your visitors and frequent buyers. It is a complex solution that often utilizes machine learning. But even Google offers a DIY guide on how to build a recommendation engine, given that your developers have the right skills. If you’re looking for faster and cheaper solutions, then there are plenty of platforms that can integrate into your store and start providing personalized product recommendations very quickly:
Take It Offline
Alright, this one seems out of the ordinary and totally out of place for this collection of tips. But it’s still a personalization technique that’s underutilized. It’s going to primarily benefit small businesses that are only starting to win over customers.
Start by personalizing the actual product that you deliver, assuming that you’re selling physical goods. When was the last time that you received a personal note from an eCommerce business? Probably a long time ago. This technique could also come in a form of a special package. Unboxing videos are a thing for a reason – people like the experience.
Data source: Dotcom Distribution eCommerce Packaging study 2016
There are also customer categories that deserve your special attention. For example, people who have made an X number of purchases or spent an X amount of money. See them adding other products to the cart but not buying? Send them a sample if you can.
The premise is similar to personalized recommendations. Only, in this case, you have to figure out a pricing strategy that works for specific customer groups. So instead of offering blanket discounts during specific seasons that eventually devalue your products or services, you can build your pricing based on your customer personas or segmentation that you defined earlier. And yes, business intelligence consultants confirm that you can also create a strategy for personalized pricing.
The good thing is that you can use the same data-driven approach that you used for segmentation to change the pricing behavior. Sometimes, it’s just a matter of adding a rule like ‘Segment A price is X and Segment B price is X-$10’. We’re oversimplifying the concept, but we hope that you got it.
Give Incentives to People Who Log In
It’s a straightforward and often potent tool that can help you learn as much about your customers as possible. This information will potentially ‘feed’ your personalization strategy and fuel other marketing activities. The premise is simple. When a user is logged in, their purchasing behavior and personal information are directly tied to their behavior on your website. There are plenty of ways to incentivize logins:
Personalize for First-Time Visitors
Over 90% of first-time visitors to your site are not there to make the purchase. That’s a mighty pie that you might want to get a piece of. It might seem impossible to personalize the shopping experience for these people, but there’s already plenty of info that you know about them.
There are also behavioral patterns that might affect your further actions towards the user. This practice is referred to as marketing automation. But in this particular instance, we’re talking about first-time visitors and personalization for them. So these specific automated events will not be applicable for people visiting the second time. Marketing platforms, such as Hubspot, also offer first-time visitor personalization. It’s all about getting them to convert during their first visit, shorten the sales cycle and acquire returned customers a lot quicker. This could be something as simple as giving a huge discount for first-time visitors. You can even tell them that to their face and see how higher discounts (within reasonable boundaries) work towards improving your conversion rates in real-time.
Data source: episerver.com
You can also use data from previous sessions for one-time or first-time visitors to extrapolate and hypothesize about the intent of those users and experiment with possible variations. For example, you see a lot of people come to the product page with a white t-shirt, but then a lot of them go to a gray t-shirt product page and eventually a number of them do end up purchasing that gray t-shirt. So instead of waiting, hit them with a discount for the gray t-shirt (that they will end up buying anyway) right from the white t-shirt product page.
Who knows, maybe they’re coming in through Google Images or some weird searches and initially they were searching for that gray t-shirt. This pattern is just a simple example. We’re sure that after digging through your data, you’ll be able to find these parallels and dependencies that will help you to personalize experiences even for people who are visiting for the first time.
There are plenty of techniques and technologies that can help you take your current personalized marketing to the next level. Starting off with a personalization strategy can help you identify the tools and resources required to pull it off. Remember that some personalization approaches are too complex to even try to envision. So either choose a ready-made solution or find a development team that has the necessary expertise to bring it to life. In many cases, an advanced personalization strategy will require advanced algorithms and involvement of AI. So plan your budget accordingly.
What kind of personalization do you use for your eCommerce website? Have you had any success with pre-packaged personalization platforms? Share your thoughts and ideas below!