How Can Artificial Intelligence and ABM be Combined to Create a Superb Customer Experience?

When was the last time you had a great customer experience? Was it on a sales call, or did it come out of an exceptional direct mail?

HubSpot defines customer experience as “the impression you leave on your customer, which is reflected in how they think about your brand, every step of the way in the customer journey”.

Customer experience has a direct impact on revenue. A positive customer experience promises satisfaction and opens up opportunities for upselling and cross-selling. Nowadays, prospects have become smart enough to spot a sales pitch a mile away. The challenge is to slowly and creatively sow your product quality and brand value in their minds so that when they are looking to buy they will think of you. Thus, it becomes imperative to offer customers an impressive shopping experience. And marketers figured it out a long time ago, which is why ABM came into being.

Account-based marketing enables B2B marketers to conduct personalized marketing campaigns for prospects. An ITSMA survey finds that 85% of marketers who measured ROI said their ABM initiatives had outperformed some of their other marketing initiatives. ABM focuses on running custom campaigns on a set of target accounts within an industry based on the attributes and needs of those accounts. With the help of ABM, marketers attempt to personalize the customer experience at every stage of the sales period. But in the age of Big Data and with the emergence of artificial intelligence, we can say with certainty that we can further improve the customer experience.

So how do you combine AI and ABM to create a great customer experience? Let’s dig into it:

ABM prerequisites — Data segmentation
Segmented data is the prerequisite for account-based marketing. Unrefined customer data is the first obstacle to an ABM strategy. The traditional marketing approach is set to reach as many people as possible, but ABM is not. A lot of marketing effort is wasted if you don’t target the right account. ABM requires segmentation at the nuclear level based on various factors to direct efforts and resources towards a defined set of target accounts.
Despite the amount of data you host, AI tools identify your most ideal prospects based on several factors precisely defined by you. AI tools work on refining, combining and structuring customer data as needed to start ABM, without having to spend a lot of time or resources on segmentation.

The transition from customer data to personalized data
Big Data has been a revelation for businesses in recent years, especially for those in the marketing industry. Almost every marketer has a voluminous amount of structured or unstructured datasets produced by the daily activities of customers that must somehow be refined and defined to derive patterns and ideas.

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The use of artificial intelligence makes this hard work economical, easy and fast. AI tools analyze data from various channels to build patterns, predict the future, and deliver valuable data insights. Once customer data is converted into personalized data, marketers will be more than ready for ABM’s success.

Personalize the buyer’s journey
Creating a positive experience throughout the customer journey across different channels is a challenge for B2B marketers. AI-powered models can be leveraged to profile which accounts are most likely to convert, after which marketers can create a personalized shopping experience across all channels to attract the right prospects at the right time with targeting specific content. Artificial intelligence also helps marketers gain insight into gaps and customer fall points in the marketing funnel.

Personalization of email marketing
Artificial intelligence takes email marketing to another level. Marketers are now better equipped to target prospects with precise timing and content to create a better chance of converting them to customers. AI has enabled marketers to run personalized campaigns for their customers based on their behavioral analysis. It is now possible to determine the best time to target prospects with personalized emails for maximum clicks.

AI and machine learning techniques improve customer service through AI-augmented messaging and email labeling. The customer service folks have a huge task reduced by AI augmented messaging by handling requests through chatbots. Likewise, AI-enhanced email markup removes the need to read all customer emails. AI tools can scan, tag, and transmit customer emails to the relevant department, saving time and focusing efforts on tasks that require human intervention.

Social Listening — Tracking Customer Feelings
It’s the age of social media and everyone is online. Social media has become an essential way for brands to determine their internet presence and to establish a personal connection with new and existing customers. AI helps marketers determine how customers feel about their brand and then target them accordingly with personalized campaigns. Social listening allows marketers to track tweets and comments relevant to their brand or product, and examine customer sentiment to target them with relevant ads and content. Social listening plays the role of a feedback form that you’ve never asked your customers to fill out. When you understand the anomalies your customers face, you can align yourself to improve your customer experience.

Continuous customer service
The customer experience doesn’t end after the sale. Do you want your customers to keep coming to you in the future? You need to provide uninterrupted customer service.

Chatbots — AI and machine learning-based tools can have a significant and positive impact on your ABM strategy. Chatbots act as tireless marketing subordinates, trained in natural language processing, to answer basic questions and establish a productive conversation with customers about your product / service and help them make decisions.

IVR — Interactive Voice Response
Traditional decision trees in an interactive voice response (IVR) system are designed to handle calls where users have one or more interfaces to create and modify decision trees. However, creating and modifying rules, logic, and instructions can be frustrating for users. The AI-powered IVR determines the intent of the customer’s request using automated speech recognition and natural language processing. In this way, the AI ​​rearranges the recommendations according to the expected flow and customer queries are resolved without any human intervention.

AI-powered robotic process automation
For a long time, traditional process automation has been used to perform simple calculations, integrate a number of systems, and perform repetitive tasks. RPA, on the other hand, has been vital in reducing manual labor, errors, and repetitive tasks like data entry in recent times.

AI-based RPA goes one step further to create accuracy and efficiency in a customer service agent’s efforts by using a cognitive engine to analyze past processes and provide probable conclusions.

Final thoughts
Applying artificial intelligence into your ABM strategy can be overwhelming and difficult for many, but it seems like it’s only expanding its influence. More and more customers are now demanding an AI-powered customer experience. When most marketing activities are automated with AI, your marketing activities are optimized, you have built a great customer experience and shortened the customer journey to close the deal.