Digital body language is a set of user behaviors on the Internet or other digital assets that, thanks to analytics and marketing tools, we can observe and adjust the way we communicate with them and also generate sales leads more effectively.
By reading the first chapter of our CMO Guide series, you already know how marketing automation solutions can help you gain valuable sales leads by making contact at a very early stage of the customer journey and also increase sales by applying effective strategies for nurturing contacts with potential customers.
From this chapter, you'll learn how to gain valuable information about your customers by observing their behavior on your website, responses to emailing and other digital assets.
In traditional communication, much more of our content is conveyed nonverbally. By analyzing body language, we can get much more information than what we hear from the interlocutor. Also in digital communication, analyzing the "non-verbal" behavior of potential customers can greatly expand our knowledge of their needs, preferences or how they make purchasing decisions.
In B2B marketing, the ability to observe and respond to digital body language messages provides the opportunity to move a potential customer from the initial discernment phase to a purchasing decision much more effectively and quickly.
It was for the needs of business marketers that the most complete concept of digital body language was designed. It was described in the book "Digital Body Language" by Steven Woods - founder of Eloqua (now part of Oracle Marketing Cloud)- one of the first and most advanced tools of the Marketing Automation class.
He noticed several years ago that the B2B buying process has become much more complicated. It involves several to a dozen decision makers who are actively seeking information on how to solve a given problem or business challenge. Each has a different perspective - the CFO will be thinking about cost, the CEO will be thinking about the overall impact on the business and the Manager initiating the buying process will be concerned with solving a specific business problem. Each decision maker will search for information using different phrases, will visit different sites or forums for exchanging information on the web.
Forrester says that about 70% of the knowledge about a product is acquired by the customer before they contact the seller. Google is of the opinion that it is about 50%. Regardless of the differences, the fact remains that the Internet is the first source of information for decision makers in B2B.
B2B product suppliers therefore need a tool to address the information needs of diverse decision makers and learn about their needs and preferences. In the early decision stages, when needs are not even specified yet, the only way to start an effective "digital dialogue" is to observe digital body language.
The purpose of observing a potential customer's digital body language is to build a profile of the customer. This profile consists of information provided "non-verbally" (digital body language observation) and "verbally" e.g. in the form of email communications, form data, inquiries, etc.
Marketers creating a customer profile should conduct an evaluation process for each of these interactions. This allows them to identify valuable prospects. "Verbal" communications will give us answers to questions about who the prospect is (name, company, position, industry, etc.) - so we can estimate positions in the decision-making process and assign an appropriate score. However, we won't learn much about his level of interest. Of course, we can ask about it, but this will be difficult and ineffective in the early stages of purchasing processes. This is where digital body language analysis comes in.
The customer has a problem
User X types "phone theft - data" into the search engine. He comes across several useful articles. One of them gives the procedure for reporting the theft and information on how to remotely erase data from such a phone. The information turned out to be useful. At the end of the article there was a link to an ebook on how to secure the phone so that in case of theft the data is impossible to read by unauthorized people. X downloads the ebook by providing his email address and name.
The customer submits the information
In this way, X turns into Ms. Catherine. We already have some basic verbal information (the query i.e. keywords, first name and e-mail address) and non-verbal information (interest in the subject of the article and the desire to protect against similar incidents in the future). An experienced marketer using marketing automation programmed a sequence of actions for Ms. Catherine, which in the first stage will identify whether she is an individual user or a business decision-maker. The prospect interacting with relevant content completes her profile.
It turned out that Ms. Catherine works in the IT department of a medium-sized company and received an urgent request to "extract data" from a phone stolen from a company employee. Since she was unable to recover the data and, thanks to our article, only managed to remotely erase it, she started looking for information on how to prepare for such situations in the future. She downloaded several more ebooks and attended a webinar on tools and processes for managing and securing data on company smartphones. After the webinar, she agreed to be contacted commercially, as she felt it was time to implement the solution presented during this online lecture. Each activity was meticulously evaluated in the customer profile. Each download of the ebook, opening of the next email, clicking on links or participation in the webinar allowed for an automatic evaluation.
Ms. Catherine's digital body language clearly indicated that she was interested in detailed information (downloading several technical ebooks and attending a webinar and agreeing to be contacted by a consultant) and that she was in a hurry - quick responses to emails and a prompt response to the webinar.
This was enough to qualify her for a sales call . Needless to say, the consultant will have a full profile of the prospect during the first call.
This information can be accessed through Oracle Profiler, a tool from the Oracle Marketing Cloud family. Thanks to this, a consultant preparing for a sales call can trace the prospect's interaction history with the content on the website, emails or the data they have provided us with in forms. We can also define the actions of a potential customer that we will be notified about via e-mail - for example, if he registers for a webinar. Such information can help us better understand the potential customer's information needs.
As you can see, observing digital body language, despite being an automated process, requires marketers to be proactive. What is needed is properly prepared content. In our case, this included several e-books of varying levels of difficulty, relevant content on the website, a technical webinar and a dozen or so emails that took the prospect through the entire process of self-education. Ms. Catherine continued to contact the company and provided basic contact information because the information she received was valuable and useful to her. The sales offer came at a time when she was already properly educated and convinced that it was worth considering an offer from a company that shares valuable knowledge.
As you can see, digital body language can only be observed if we are able to attract and keep the customer engaged in the process of self-education.
This is possible by using modern Marketing Automation tools and having valuable content designed to enable proper search engine visibility and guide the potential customer from problem to solution.
Contrary to popular opinion, this is not an Orwellian surveillance machine but a way to have a valuable dialogue and exchange of information with a potential customer who is looking for a solution to their problem. Using this tool will only be effective if we are willing to educate customers and share valuable knowledge with them.
Read more:
Digital Body Language link to Ebook in Amazon store
Mini site by Stewen Woods - author of Digital Body Language
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