When was the last time you had a great customer experience? Was it during a sales call, or did it pop out of an exceptional direct mail?
HubSpot defines customer experience as "The impression you leave with your customer, resulting in how they think of your brand, across every stage of the customer journey."
Customer experience has a direct impact on revenue. A positive customer experience promises satisfaction and opens up-sell and cross-sell opportunities. In today's times, prospects have become intelligent enough to sense a sales pitch from a mile away. The challenge is to slowly and creatively plant the seed of your product quality and brand value in their mind so that when they're looking to buy, they think about you. Thus, it becomes imperative to provide customers with an impressive buying experience. And marketers have figured this long ago, which is why ABM came into existence.
Account based marketing is enabling B2B marketers to carry out personalized marketing campaigns for prospects. An ITSMA survey reveals, 85% of marketers who measured ROI said their ABM initiatives outperformed some of their other marketing initiatives. ABM focuses on running personalized 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 are trying to personalize the customer experience at every stage of the selling period. But in the age of Big Data and with the emergence of Artificial Intelligence, we can safely say that we can further enhance the customer experience.
So, how can AI and ABM be combined to create a superb customer experience? Let's dig into it:
ABM Prerequisite - Data Segmentation
Segmented data is the prerequisite for account based marketing. Unrefined customer data is the first roadblock for an ABM strategy. The traditional marketing approach is defined to reach as many people as possible, but not ABM. A lot of marketing effort is wasted if you are not targeting the right account. ABM requires a nuclear level segmentation based on various factors to direct efforts and resources at a defined set of target accounts.
Despite the amount of data you are harboring, AI tools identify your most ideal leads based on several factors defined by you with precision. AI tools work on refining, combining, and structuring customer data as needed to kickstart ABM, without having to spend a lot of time or resources on segmenting.
The Transition from Customer Data to Custom 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 data sets structured or unstructured, produced by day-to-day customer activities that have to be in some way, refined and defined to derive patterns and insights.
The use of artificial intelligence makes this arduous job economical, easy, and quick. AI tools analyze data from various channels to establish patterns, predict future, and provide valuable insights into the data. With customer data converted to custom data, marketers will be more than ready for ABM success.
Personalizing Buyer Journey
Creating a positive experience along the customer journey across various channels is a challenge for B2B marketers. AI-based models can be leveraged to profile accounts that are most likely to convert, following which marketers can create a customized buying experience across channels to attract the right prospects at the right time with precision content targeting. Artificial intelligence also helps marketers get a good look at shortcomings and where customers are falling out in the marketing funnel.
Customizing Email Marketing
Artificial Intelligence is taking email marketing to another level. Marketers are now better equipped to target prospects with a precision of timing and content to create a better chance of converting them into customers. AI has enabled marketers to carry out 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 to get maximum clicks.
AI and machine learning techniques are augmenting customer service with AI-augmented messaging and email tagging. Customer service people have a huge task cut out by AI-augmented messaging by handling queries through chatbots. Similarly, AI-augmented email tagging cancels out the need to read every customer mail. AI tools can scan, tag and forward customer emails to the concerned department, saving time and focusing efforts on the tasks which require human intervention.
Social Listening - Tracking Customer Sentiments
It is the age of social media, and everybody is online. Social media has emerged as an essential medium for brands to determine their presence on the internet and build a personal connection with customers, whether new or existing. AI is aiding marketers to determine customer sentiments toward their brand and then target them accordingly with customized campaigns. Social listening is enabling marketers to track down tweets and comments relevant to their brand or product, and review customer sentiments to target them with relevant ads and content. Social listening plays the role of a feedback form you never asked your customers to fill. When you understand the anomalies your customers are facing, you can align yourself to improve your customer experience.
Continuous Customer Service
Customer experience doesn't end after the sale has occurred. Do you want your customers to keep coming to you in the future? You should provide uninterrupted customer service.
Chatbots - AI and machine learning-based tools can make a significant and positive impact on your ABM strategy. Chatbots act as a marketer's tireless subordinate who is trained with Natural Language Processing, to address basic queries and establishing a productive conversation with customers about your product/service and help customers in making decisions.
IVR - Interactive Voice Response
Traditional decision trees in an interactive voice response (IVR) system is designed to manage calls where users are provided with one or more interfaces to create and modify decision trees. However, creating and editing the rules, logic, and instruction can be frustrating for users. AI-powered IVR determines the intent of the customer request by using automated speech recognition and natural language processing. In this way, AI reorders recommendations as per the expected flow and customer queries are solved without any human intervention.
AI-powered Robotic Process Automation
For a long time, traditional Process Automation has been used to carry out simple calculations, integrating a number of systems and carry out repetitive tasks. RPA, on the other hand, has been vital in reducing manual work, errors, and repetitive tasks like data entry in recent times.
AI-powered RPA goes a step further to create accuracy and efficiency in the efforts of a customer service agent by using a cognitive engine to analyze the past processes and provide probable conclusions.
Concluding Thoughts
The application of artificial intelligence in your ABM strategy can be overwhelming and challenging for many, but it looks like it is only expanding its influence. More and more customers are now demanding AI-driven customer experience. When most marketing activities are automated with AI, your marketing activities are optimized, you have built an exceptional customer experience, and shortened the customer journey to close the deal.