From Passerby to Customer (phase 2: looking)

In this article we will discuss the "looking" phase of the E-commerce Performance Model. Once you are found, you also want to maintain this targeted interest with your visitors at the right time.

We elaborate on the drivers that play an important role in sustaining this goal-directed interest. We also discuss two typical performance indicators that occur in the "looking" phase.

Stages of customer journey and partial conversions

In the previous article we discussed dividing the customer journey into different phases. For phasing the customer journey for webshop visitors, Vicus uses the E-commerce Performance Model which includes the following 5 phases:

• Coming
• Watch
• Choosing
• Buy
• Returning

Before visitors make a purchase they go through a number of phases: from coming to look, from looking to choosing and from choosing to finally buying. And because we want to have returning customers we also go through the phase from buying to (returning). It is important to see which sub-conversions need to take place in order to move a stage forward. When we know how to identify these partial conversions, we can also measure them and take action.

Targeted interest retention

A good webshop receives visiting traffic in different ways. For example, visitors enter through the homepage, but also through (sub)category pages, information pages and, of course, product pages. If you have a broad assortment as a webshop, you can make these products individually findable in search engines. As a result, category and product pages suddenly function as landing pages. Landing pages are often pages that are a bit deeper in the structure of the website and refer to a product category or a specific product. It is desirable to measure the bounce rate for all modes of entry.

When visitors come to your website through one of these ways (phase 1 come) you want to keep them of course. After all, your visitors are looking for specific products and in that search they came to your webshop. This targeted interest is extremely valuable and you should facilitate it as much as possible. Suppose the visitor comes to your web shop during his search but cannot find the product immediately, he will have to search your website. This takes him out of his earlier thinking about the problem he wants to solve and the product he is looking for for that. He is now trying to figure out how to search on your web shop. If this happens regularly on your web shop, you will see the bounce rate increase and the conversion decrease.

Bounce rate and channel conversion as indicators

Bounce rate makes conversion measurable

If you want to measure the conversion from "coming" to "looking" you need to focus on the percentage of visitors who actually view your products. Which visitors actually view your products depends on the targeting of your campaign and your offer. But also how good the speed, navigation and usability of your website is.

A good indicator of whether you are getting the right audience on your Web site is the bounce rate. The bounce rate is the percentage of visits in which only one page on the website is viewed. This performance indicator clearly maps out whether you are not only being found in the coming phase, but that you also manage to generate interest among your visitors in the "looking" phase. After all, when a visitor views more than one page, they have at least encountered enough information of their liking not to leave immediately.

Bounce rate is a critical performance indicator for online shops. It is then wise to look at the bounce rate per channel that generates traffic for your webshop. Especially channels for which you pay (advertisements), it is good to measure the bounce rate and keep it low. Otherwise, you are paying for traffic that is not interested in your offer.

Calculate conversion by channel

Typical channels for a webshop are search ads, banner campaigns, newsletters or mailing that you send out. You can calculate the effectiveness of these channels using the performance indicator channel conversion. For each channel, you follow the visitors through to purchase and you divide that by that and then you have the channel conversion. For example, channel conversion is the number of orders from a specific channel divided by the number of visits from that same channel.

Let's calculate this in an example. For example, you get 300 website visitors from your mailing and then 5 orders from these visits. The channel conversion of this mailing is then 2.5 percent. If you compare the channels with each other, you can immediately see which channel has the highest return. This allows you to better determine where to put your efforts.

An important condition is that you need to know your target group well if you want to measure the return of those channels purely. You need to know what your target group is looking for and where they are in the customer journey. So mapping questions, needs within the customer journey is an important starting point for the pure measurement of return.

Identify dropout moments

Bounce rate as a signal

So a low bounce rate is an indication that you are receiving the right audience. But conversely, it is more difficult to interpret what exactly a high bounce rate is as a signal. Are we dealing with the wrong target group or is there more at play? In this case, we should see bounce rate purely as a signal because it can mean several things. How do we know for sure that a high bounce rate is due to the wrong target group or a wrong website.

This is a pretty important question and the only way to get this clear is to test it. For this you can use tools for A/B testing or you can use heatmaps of your website to follow and interpret the behavior of your visitor. Only then you can better explain and interpret the signal of a high bounce rate.

Content, navigation, information and speed as a driver

Identifying dropout moments and their underlying drivers is what we do at each stage of the E-commerce Performance Model customer journey. Ultimately, you use these drivers to drive the targeted interest of your visitors (from the right target group) to the next stage. Here are some examples of drives.

Information and Content

Some pages seem to target multiple audiences. The result is that the page is overloaded with text and elements. As a result, the visitor no longer knows what the page is trying to clarify or which actions on this page are interesting for him. The visitor leaves the page and thus increases the bounce rate of that page. This incident says nothing about the quality of your target group. Here, the content and information offered plays a clear role.

Speed

Some pages on websites load slowly. This may be because a lot of "heavy content" is used. Think of content such as images and video that is insufficiently optimized. Another possibility is that the technology of the website is insufficiently optimized. Maybe there are too many active scrips or caching issues on your website. Again, the result is that visitors leave the page prematurely and thus contribute to a high bounce rate.

Navigation

Suppose a visitor lands on a product page through a search engine query, but that product is not what the visitor is looking for. Then you want to guide the visitor to the right product in the best possible way. Navigation then plays a crucial role. Because how do you end up on the right (product) page. Known ways are offering a search box or using breadcrumbs. If you miss these kinds of navigation elements, a visitor will feel lost and leave your website.

Summary

In this article, we discussed the second phase of a customer journey of the E-commerce Performance Model for:

• Interpreting the performance indicators "bounce rate" and "channel conversion";
• naming multiple inputs to your web shop;
• Maintaining purposeful interest;
• Recognizing drivers in dropout moments.

The next phase of the customer journey in the E-commerce Performance Model is the "Choosing" phase. In this phase, we go deeper into how to help the visitor in making a final choice towards purchase.

Below is an overview of articles by phase in the E-commerce Performance Model:

• From passerby to customer : coming
• From passer-by to customer : watch
• From passer-by to customer : choosing
• From passer-by to customer : buy
• From passer-by to customer : coming back

Also interested in the critical performance indicators for web shops and where you use them within your customer journey? Perhaps you already use performance indicators, but do they measure the right things for your webshop? Feel free to contact us to discuss this.