Draw Your Customers Back By Analyzing Dynamic User Behavior

satisfied-customers transparency

When customers or visitor leaves your website without performing any action that will lead to a sale, it implies that your webpage is devoid of one or two elements that is compelling enough for them to be part of your consumer base.

Some tend to let this non-conversion slip and move on to find a new customer that will be more interested in what they have to offer. In these instances, why not consider an unconverted visitor a potential customer? After all, to chance upon your website amid the hundreds of million others out there signifies that you have something they are looking for (albeit lacking a couple of elements).

This article aims to show you how to analyze dynamic user behavior and pinpoint at which stage your customer left and why. It will also include actionable steps on how to remedy these issues.

Why Is Customer Behavior Data The Key To Business Success?

You know what products your customers purchase. You know, based on past records, when they usually buy it. But why not go deeper on the ‘why’?

According to an infographic from Customers That Stick (CTS), some 82% of US-based customers cite poor customer experience as the main reason that prompts them to stop doing business with a company. Factors that were most raised as making for a bad customer experience were due to a rude staff (73%); issues unresolved in a timely fashion (55%); and unknowledgeable staff (51%).

Today’s ubiquitous social media platforms enable customers with bad experiences to spread their stories in the digital world, warning others to keep away from an unfriendly brand.

Meanwhile, customers choose to stick with brands that have a good reputation, the CTS added. Aside from this factor, consumers also retain their relationships with companies that have friendly customer assistants, can easily provide needed information, and is personalized.

But how do we meet those standards?

Analyzing User Behavior

The McKinsey & Company reported that organizations that treasure customer insights outpace competitors by 85 percent in sales and more than 25 percent in gross margin.

Hundreds of giant tech firms like Amazon and Google have invested in customer analytics. But the practice is not exclusive to billion-dollar firms, as even you can leverage on knowing your customers’ behavior.

Here are a few ways you can do so that does not translate to hefty marketing cost:  

#1. Use Customer Behavior Data to Improve Customer Acquisition

The 2018 Data & Analytics Global Executive Study and Research Report by MIT Sloan Management Review, which surveyed more than 1,900 business heads and analytics experts, said more than half or 59% of respondent are now using analytics to gain a competitive advantage. This is higher than the 51% posted in a 2015 survey.

It is worthy to note that the survey found only 49% being able to use data to guide future strategy. So how did this discrepancy arise?

The MIT Sloan Management Review, citing responses from interviews with company managers, said the easy access to data today has indeed allowed companies to deal with large data. However, only a few may prove to be helpful.

“As you add data, things change. It is a living environment, and you have to keep up on it.” Bruce Bedford, vice president of marketing analytics and consumer insights at Oberweis Dairy Inc., was quoted in the review.

Entrepreneur advocacy blog site NegoSentro suggests that marketers use Proof Business Impact Analysis Tool, a data analysis tool that allows businesses to map out contingency plans as it aims to provide the causes and effects of decisions businesses can undertake for a more robust performance.

#2. Analyze Your Customer’s Post-Purchase Behavior

According to B2B Marketing, a repeat customer will result from the satisfaction they feel upon purchase of your product.

This satisfaction (or dissatisfaction) does not only play a significant role in reeling the customer back into your radar, but may also be shared in the online space through web reviews or social media.

Companies should create positive post-purchase communication, in order to engage customers and make the process as efficient as possible.

RedStagFulfillment suggests making seasonal buyers into regular ones by keeping in touch with them through e-mail. You should, however, refrain from e-mail blasting and instead offer other e-mail marketing campaigns such as creative, educational, or customer experience e-mails to get them hooked.

#3. Analyze Device And Channel Use Of Customers

Knowing which device—say, mobile or computer—is most used for a conversion will allow you to dwell on the issues that stops customers from making a conversion on other devices.

You can compare each device’s performance in terms of click-through rates, pay per view, and actual purchase transactions. A device that logs lower in one of these areas may be having issues on page visibility, page load time, page scripting, and page navigation, among others.

Meanwhile, according to e-commerce leader Shopify, knowing which online channels your consumers spend most of their time gives you leverage on how to get their attention through that platform. The e-commerce leader further suggest that you experiment with channels that best fit your audience.

#4. Analyze Visitors Bounce Rate And Exit Rate

A bounce rate refers to online visitors who left your site immediately without navigating other pages, while an exit rate covers visitors who careened through your site page by page but still left your page without converting.

Failing to differentiate the two can lead to wrong data analytics. To find out how your page performed in terms of these two KPIs, Growth Funnel provided a simple equation for you to understand how to address these non-converting visits:

 

  • Low bounce and low exit = “splendid” page
  • Low bounce and high exit = “decent” page
  • High bounce and low exit = “something is wrong”
  • High bounce and high exit = page requires “urgent attention”

 

#5. Analyzing Customer Lifetime Value

A customer lifetime value is the profit you estimate to gain from the purchase transactions a customer will be making with you during their lifetime.

This sheds light on when you can see the return on your investments, as well as help you improve your business decisions regarding sales, marketing, product development, and customer support.

To find out how this works, take a look at one of the most successful on-demand video streaming companies today.

According to Barn Raiser, Netflix estimates that its average customer subscribes to its services for two years and one month. This puts the lifetime value of a Netflix customer at $291.25. Analyzing these figures helped Netflix come up with tactics that cut down their churn rate to 4%.

Takeaway

Indeed, data analytics is changing the landscape of how business players think. Succeeding in this tactic guarantees a boost on any company’s margins, as it has the power to convert the most indifferent visitors to be part of your loyal user network. Although seeing the completion of a purchase journey requires a lot of patience on your part, data analytics can contribute in making that transaction materialize.