Chatbots are a common feature of modern websites. Many B2B businesses now understand the value that a chatbot offers, so there is a surge in demand for such solutions, especially in the marketing sector. According to industry research, about 15% of buyers have used a chatbot to communicate with a business in the past year.
However, when it comes to ABM or the Account-Based Marketing approach, the extent of engagement differs from what you strategize during other promotional campaigns. It is a customized approach to marketing that allows organizations to target specific profiles. These accounts can be top-level executives or prospects that may end up offering business to the organization.
The level of personalization is high, and it enables businesses to improve product awareness among leads, which can drive their purchasing decisions. In addition, the creative content created during the ABM campaigns is in sync with the targeted profiles’ specific pain points.
However, engaging targeted profiles through content is an excellent approach; you will have to predict the mindset of an account. This is where a chatbot can help you with AI-based algorithms that gather data from targeted profiles through questionnaires, analyze them, and offer insights into their specific issues.
So, let’s see how you can build a chatbot for your ABM campaigns? But before we do that let’s understand what a chatbot is?
A chatbot is a computer program or software that mimics human conversations through speech recognition and Natural Language Programming(NLP). It stimulates the interaction between humans and machines in a way that is close to what people do in routine life.
The conversational capabilities of chatbots can be leveraged by marketers to generate leads and conversions. In addition, you can use chatbots to engage your target audience for better data capture and use AI-based algorithms for content suggestions.
There are several use cases for chatbots for marketing automation also. For example, you can use chatbot forms that ask for specific information through data inputs. It merges the gamification approach with the human-to-human-like interactions to enable higher engagements. Such chatbot forms can help identify critical targets for your ABM campaigns and then suggest relative content to these profiles based on that data.
However, one of the essential elements of any chatbot is its architecture that allows organizations to execute their marketing logic for target profiles. So, let’s discover what the architecture of a chatbot for your ABM campaigns is.
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The first step towards building a chatbot is to decide on what is the use case? The pre-defined usability will ensure that you make a custom logic that aligns with your ABM goals.
It is like deciding exactly what you will expect from the chatbot to deliver? For example, if you are pitching the chatbot upfront for an ABM profile to have a conversation, problems similar to this can start by asking questions about pain points.
Once the profile specifies the pain point like scaling issues or database management problems, the chatbot will suggest the content of the projects conducted by your firm to solve similar issues for your clients. Irrespective of what are the pain points, chatbots can ask for data about the size of the profile’s organization.
These two factors- team’s size, and relevancy of pain points can qualify a lead to either go to a human for closing the deal or offer relevant content for the top of the funnel profiles. Apart from this, there are several possibilities for the usage of chatbots.
However, whether to build a chatbot or not for your ABM campaigns also depends on the budget and scale of the promotional program. But, before we discuss these aspects, let’s discover more about the chatbot architecture.
A chatbot’s architecture establishes its functionality and response to the user’s request for data. Behind the scenes processes for chatbots deal with data access and executing the business logic during the interaction with an ABM profile.
Receiving the user request for data needs a medium like websites, applications, or even software. Once the data request is placed through voice, text, or other inputs, the Natural Language Understanding(NLU) model analyzes it to identify the user’s intent. Once the algorithm embedded in the chatbot architecture gains a high confidence score on the user’s intent, it has to decide the further course of interaction.
For example, an ABM profile related to a startup wants to know about different ways in which they can gain funding for their business? Once the chatbot identifies the intent of the profile, it retrieves the information from the database related to similar use cases within the organization, which can help promote your services and offer value to the profile.
At the same time, If the chatbot offers data from an external source, it uses API calls to create a data exchange between heterogeneous systems. The entire conversation is managed through dialogue management systems that save every data. Now that we have a basic idea of how a chatbot architecture functions, let’s look at some types of chatbots that you can leverage for your campaigns.
There are several different types of chatbots that you can build for your ABM campaigns. Some of them are based on pure interactions while others form inputs and questionnaires. Understanding the types and functions of these chatbots is essential for their usability and the extent of budget you will need to build them.
#1. Contextual Type– It is a type of chatbot that leverages Artificial Intelligence and Machine Learning. Algorithms try to identify the user’s intent and analyze them. They also save unique searches for each user for references.
#2. Keyword Type– It uses the concept of keyword search along with advanced NLP to power search-based interactions. The chatbot offers content suggestions based on the keywords that your ABM profiles may perform on different platforms.
#3. Voice-based– These are chatbots that receive user requests as voice inputs through smart devices, apps, or websites. Identify the exact intent through speech recognition and then leverage empirical patterns to offer data.
#4. Service-based– It uses the service request as input and asks several questions related to it. The type of service interacts with the user for data exchange and execution of specific tasks.
Chatbots can be the future of ABM marketing if executed well. However, you will need to work on several aspects of building such an intelligent solution like identifying profiles, offering the data on profiles to bot algorithms, and even creating an architecture that offers rich interactions. Thus, while it may seem easy on paper, you will need reliable solutions to counter the challenges of building a chatbot for marketing campaigns.