Strengthen customer service with behavioral targeting
Behavioral targeting allows you to reach consumers with personal, relevant information, based on online behavior. If you also use that for live chat, you can use this channel much more efficiently.
If you buy a lot of black leather clothing online and you like to watch heavy motorcycles, then ads and content aimed at you will be in this corner. The goal of behavioral targeting is to personalize ads and content to increase relevance. But there are more possibilities with behavioral targeting, in this article, I will explain one of them.
Don’t send, receive information!
Behavioral targeting focuses on sending information that is as relevant as possible. The emphasis is on sending information and not on receiving information. In recent years, companies have increasingly realized that it is important to learn from consumers and that selling starts with a conversation with potential customers. Therefore, behavioral targeting should not only focus on sending information, but also on increasing the relevance of obtained information. Let this also be possible. You can do this by offering customer contact in an effective way, for example with live chat.
Shop assistant ingenuity
Livechat can be seen as the online translation of the physical shop assistant. The chat makes it possible for website visitors to ask questions while shopping online. When you are shopping in a physical store, at a certain point the shop assistant comes to you and offers his or her help: “Good afternoon, can I help you with something?” Online, this greeting translates into a chat window that pops up proactively.
The offline and online situation are not exactly the same. It can be a problem for the physical shop assistant if five potential customers, separately from each other, walk into the store at the same time. The vendor has to choose who to offer help to. The seller scans the shoppers and sees who has the most intention to buy: selling instinct. The online seller (chat operator) does not have this problem, because he can have multiple chats at the same time. The only question is whether you want to start a conversation with everyone online, and at what time.
Behavioral targeting is basically the online translation of the seller’s instinct. It determines who needs assistance:
Based on how a website navigates visitors
Based on previously shown online behavior
When and where this help can best be provided.
A combination of different criteria (e.g. order value, location, current URL) determines to whom and when the proactive greeting is shown.
The search for targeted customer contact with chat
In most cases, Livechat is placed on the entire website, from the homepage to the blog. The result is that visitors ask a wide range of questions, with the risk that there will be customer contact in which you would rather not invest time. A chat conversation started on the blog page is a student who is looking for specific information for his school assignment 95 percent of the time.
For example, we chat for a car tire supplier where we are only on the appointment and order module page. These are moments where you want to assist the potential customer to ensure that the customer converts. Throwing the chat on every page of your website is not always wise. More is not always better. You can choose to place the chat on specific pages, but another solution is behavioral targeting.
Increase efficiency with behavioral targeting
Behavioral targeting helps you to deploy the crew of your live chat more efficiently. The chat window no longer appears with every visitor, but only with visitors who show the intention to convert. Has the visitor been on your website twice in the past week and is he or she looking at the same lease car as during the previous visit? Then there is a good chance that there is serious interest.
With behavioral targeting, the percentage of chatters will decrease, because not everyone on the website reflects a high buying intention. At the same time, the percentage of visitors that chat compared to the number of visitors that receive a proactive greeting will increase. In short, in absolute terms you get fewer chats but the chats you get are more valuable. Your chat operators are therefore deployed more efficiently and can work more effectively because visitors have more concrete questions. The result is a positive influence on your ROI.
Behavioral targeting can be applied in two ways
As with any implementation, behavioral targeting starts with a goal. This can be a conversion rate of visitors who chat increase to 15 percent’. With behavioral targeting you can work on this in two ways:
You determine the success factors that visitors you want to chat with have to meet (chat-triggers).
With a self-learning algorithm that determines who will see a proactive greeting (algorithmic).
Behavioral targeting by means of chat triggers means that you set the behavior of a visitor that will see a chat window. Analyze the behavior of visitors with concrete interest and visitors who drop out. This is important to determine when the chat will appear. You can do this by analyzing the customer journey of visitors and looking at moments of withdrawal and success factors. As described above, you can assume that visitors who have watched the same product page several times have a concrete interest when viewed. Visitors who place a product in the shopping cart and leave it later are also potential customers that you want to get in touch with.
This are two examples of essential moments when you want to help visitors convert. You can also only support potential customers who show high potential value. For example: on a travel agency’s website, our chat only comes up when the ordering process starts with an order value of more than 120 euros.
Behavioral targeting using chat triggers works well when you know which visitors you need to help you increase conversion when. If your data and target group are not clear enough to work with manually, then the next option is a better idea.
Another possibility is to use an algorithm to analyze the behavior of visitors and to determine on this basis which visitors will see a chat. The algorithm identifies the behavior of different types of consumers and learns from the behavior by looking at when visitors convert and when they do not convert.
Working with a self-learning algorithm means that you do not manually set criteria that determine when a visitor sees a chat window. The algorithm recognizes when a visitor is about to leave your website when the chat window shoots up to offer help. Self-learning algorithms become more reliable and better as more behavior is analyzed.
If many of your visitors leave the website after looking at a product page for more than one minute, the algorithm understands that visitors should be contacted after 45 seconds. This example is fairly straightforward, but it is also possible that after following a certain path, visitors mainly leave the website. Apart from the fact that they probably couldn’t find the right information via this customer journey (marketing insight), it is a signal that visitors need help during this route.
The idea behind behavioral targeting is to create a customized chat solution. Each contact channel has its own strengths and weaknesses. Helping visitors fill in forms is much easier by phone than via chat. Do not offer a chat on these website pages. However, if you want more certainty that large orders convert, then support visitors at these times with chat. Behavioral targeting is an innovative solution to deal with this efficiently and effectively.