What Does 'Bad Data' for Ecommerce Personalization Mean?

In 2018, ecommerce personalization is more than a passing fad.
It is the difference between forging a connection with your customers and letting potential online sales slip through your fingers. The best laid plans and most attractive websites may generate some attention.
But to close the deal, you must make your customers feel like they are the only one in the store. They must believe that your brand cares about them and knows how to serve their needs like no other brand possibly can. Ecommerce personalization allows companies to achieve this.
It does that by enabling online retailers to use data insights to tailor their service. They cater to segmented groups of their audience by offering targeted content and personalized product recommendations people actually want to see.
This personalized service builds a better online shopping experience, which helps build a bond between your business and its customers. It is not a fad. It is the future of ecommerce. Competition is just too intense to ignore that simple truth now. The problem for many companies, however, is they don’t know how to harness this potential.
Using personalized product recommendations has many great benefits, which can save your company time and money.
However, it all comes down to how you use your data.

How Can You Know The Difference Between Useful Data and Bad Data?

Using the right data is just as important as collecting it, if not more.
Kissmetrics claim that an organization can generate a 70% boost in revenue over another organization, purely based on data quality.
Intelligent analysis of data on customer behaviors allows companies to leverage the insights to drive their personalization strategy forward. This turns information into a better ROI for the marketing efforts of the company.
It’s overwhelming for marketers to receive such massive amount of data. However, you really just need to laser focus your attention on a small subset of that. Finding the right data begins with what is most apparent in that moment.
Imagine you’re a sales assistant in a physical retail store. A customer comes up to you to ask where the men’s shirts are. Before you send them off on a wild goose chase, you’d want to know for sure that you direct them to the right aisle. To do this, you’ll need a little more information about what it is they really want to find.
By asking some strategic questions, you can get the simple answers about the style and color of shirt they’re interested in, and then give them the precise directions they need.
You wouldn’t waste any time asking them irrelevant questions about their favorite type of hat or where they’re going on vacation next summer.
In ecommerce, there is an equivalent of these irrelevant questions. They come in two forms:

  • Outdated data
  • Inadequate data

When a company has an overload of these types of data on file, they can run into some issues that hamper the user experience.
There will always be some degree of error rate, but successful ecommerce personalization should try to keep that rate to a minimum.

What Is Outdated Data and What Can Ecommerce Companies Do About It?

Ecommerce is a rapidly changing industry, with incredible advances in machine learning and AI changing the game constantly.
In addition to that, customers have a growing expectation for immediate satisfaction, and expect digital services to streamline the online shopping experience. That all makes for one tough industry to succeed in. Remaining agile is key.
People may visit a site to book a jungle safari holiday with your company once, but that doesn’t mean they want to be inundated with offers for more jungle safari packages every time they visit your site.  Offering outdated recommendations based on older data will only frustrate the customer, with 95% of customers likely to leave your site if they get poor search results.
Companies must understand the needs of their customers in the moment and respond to their behaviors to make real-time recommendations.
The more data you acquire and analyze, the more accurate you will get with your real-time recommendations. And personalization increases the chances of conversion by 75%For successful ecommerce personalization, your company must have a recommendation engine that is able to recognize visitors instantly. It also must be able to serve up personalized product recommendations that the customer still wants.

What Is Inadequate Data and What Can Ecommerce Companies Do About It?

If we are going to understand precisely what our customers want, we must know where they are coming from when they arrive on our site. This requires greater insight than their on-site behaviors.
You must have clear access to the channels they are referred from, including information on:

  • Social media channels
  • Organic search results
  • Whether they are first-time visitors, or if they are frequent shoppers who are returning to your online store.
  • Their favorite categories
  • Their preferred brands

When we look at the data recorded by analytics programs, there are two complementary analytics that let us know more about a buyer’s journey:
Click data and engagement data.
These are often confused.
Although click data tells companies what pages on their website are performing well, without the engagement data, it is difficult to know what the customers are really interested in.
Having inadequate data that limits the insights on the customer makes it harder to offer relevant product recommendations. Many ecommerce companies overlook the value of this non-click behavioral data, which means their efforts for ecommerce personalization are hampered by only having part of the picture.

Machine Learning is the Answer

The solution to this problem is continuous machine-learning.
If your personalization engine continuously collects and memorizes visitor data for each individual visitor, your personalized product recommendations for each visitor will become more accurate over time. As it gathers data, the algorithms will get smarter, and can boost revenues by 20% or more.
By putting the customers in focus, and analyzing their behaviors on your site, ecommerce companies can learn a lot about how to serve their customers. The more data you gather, the more refined and accurate your service will become.
 
 
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Keywords: Ecommerce personalization, personalized product recommendations