If you ask any marketer what their ultimate goal is beyond just improving sales, chances are you will hear them say something about improving the customer experience. After all, these two priorities are tightly related. Dimension Data’s Global CX Benchmarking Report found that 84% of businesses that improved their customer experience saw a direct growth in revenue as well.
Marketers must know when and how to meet their customers, what content to show them, and how to keep consumers engaged. This is particularly true for B2B marketing since the targeted audience pool is much narrower and more focused. All of this requires real-time data insights along with strategies to successfully turn information into action.
According to a Statista report, 31% of marketing organizations stated that a dearth of real-time consumer insights was the greatest barrier to improving the CX. Additionally, 22% struggled with finding technology for data implementation, while 19% admitted that they simply lacked basic knowledge when it came to improving or even influencing the customer journey.
Thankfully there is a solution:
The term “martech” is a portmanteau combining the terms “marketing” and “technology.” As such, martech represents the intersection of marketing and technology in today’s highly digital business world. Any type of technology that has a bearing on marketing operations can be called “martech” whether it is a part of an analysis platform, a device-facing benchmark tool, or any other type of digital or high-tech resource.
Modern marketing is driven by software, automation, and data and most B2B companies have a “martech stack” of their own. Machine learning algorithms and models power SaaS tools that allow marketers to seamlessly gather, analyze, and integrate key data into their strategies, and craft the most favorable response to customers, at every stage of the marketing funnel.
Let’s dive into the nitty-gritty of how AI-powered martech transforms the customer experience and makes the customer journey painless – even delightful – with a little human touch.
Understand and Organize Customer Data Using Martech
One of the most unique features of AI is its ability to gather and analyze data almost instantaneously. Martech tools can help organize key data from all points of the customer journey, such as:
- Web and app interactions
- Customer service experiences
- Social media engagement
- Product usage – trials and post-purchase
- Returns or complaints
- Changes to a user profile or account information
This creates a full, robust picture of how customers get from point A to point B, along with all of the stops (and marketing opportunities) in between. This results in data unification for a more singular customer view which can help marketers truly understand their target audience.
This is crucial for the B2B customer experience, as it is rarely straight forward. It generally takes up to eight separate interactions before a prospect becomes a sales lead. In order to push that lead to become a paying customer, marketers can use AI-based tools to analyze data and set the course of action for all of the above types of interactions, such as:
- Product recommendations
- Natural language processing in conversational chatbots for customer service
- Advertising and content delivery
- Predictive modeling of demand and usage
- Dynamic pricing and credit scoring for loans
- Estimating transaction volumes
Personalize All Interactions
Oftentimes, personalization is geared towards B2C strategies with customized ads, emails, or promotions. However, personalization is equally as important to B2B customers. Personalization is how AI affects the customer journey most directly. After all, customized experiences can only be created with loads of data to back them up.
Personalization improves the customer journey by making it easier for the lead to move towards a conversion.
For instance, AI enables the dynamic tracking of customer profiles and their interaction with various brands. It then builds a journey map of which type of marketing interaction to send next based on their past actions. And it can track third-party data.
Say a lead lands on your website thanks to a targeted online ad. They read one of your blog posts. They are then moved to enter their email to download a report about your product then exit your site.
Based on this data, AI customizes your next interaction with that customer. You could send them a customized email based on their reading preferences. Their business email also gives you information on their company’s industry and presumed pain points, making the email even more relevant.
Personalization is also not limited to each individual; larger marketing interactions can be customized, too. For instance, one way to improve your B2B content is to base new topics on search data. AI helps you to identify what information your audience needs to move from one step to the next, you can create a “customized” content selection that addresses their questions and concerns.
Analyze Customer Feedback and Conversations
It is important to understand what your customers really think about your business and know what they want to improve the experience. According to one survey, 76% of customers stated that the most important thing that could improve their experience with a brand was for companies to “understand their needs.” Over half of the respondents also expected businesses to improve by following through and taking action on their feedback.
Listening to customers is clearly a key part of improving their experience. However, brand-consumer or consumer-consumer conversations are not just happening with customer service reps or via feedback surveys. They’re happening virtually everywhere on the internet. It becomes next-to-impossible for marketers to analyze, prioritize, and respond to them all within optimal time windows. Thus, one of the most effective ways to effectively analyze interactions, feedback, and conversations is to feed them all into AI-based analysis models.
AI doesn’t stop at what consumers are saying about your brand. It goes one step further to analyze how they are feeling about you. Sentiment analysis is a process that makes sense of your customers’ opinions and thoughts by actually analyzing conversations directly. This includes creating AI-powered chatbots to prompt conversation signals, such as:
- What is the issue you are experiencing?
- What information are you looking for?
- Do you want us to approach this issue in a specific way?
- Have we helped you solve this problem?
- How can our business improve and serve you better next time?
From here, sentiment analysis can create detailed reports to give marketers an accurate picture of the pain points customers are experiencing. While it is still up to marketers to take action and make improvements, the tool simply gives them all the data they need to make an informed decision.
Predict Future Behavior
In the past, marketers have had to make educated guesses for the next financial quarter or year based on past data. Thankfully, AI-based tools make it much easier to gain an accurate insight into future trends and predicting customer behavior.
As per a study by Narrative Science, 38% of marketers agree that the most important service AI can offer is an accurate prediction of consumer behavior. Machine learning models have the unique ability to create dynamic predictions, taking into account hundreds of variables or fresh data as it becomes available. This provides marketers with real-time information that can be used for instant actions.
Deep learning algorithms uncover patterns within patterns in everyday human behavior – what we tend to eat, how we drive, what movies we watch, how much we spend on our hobby projects, everything provides fodder for automated, hyper-personalized targeting as well as “social prediction.”
AI can harvest conversational data gathered by social media listening tools and run it through sentiment analysis models to identify patterns and forecast audience behavior – either individually or in groups – months in advance.
By knowing what your customers want or what their next steps will be, you can create a smoother journey for your customers. Here is an example of how AI can help you:
Your AI system predicts that the churn rate of your SaaS product might increase within a specific audience segment due to upcoming regulatory changes in your industry. You could create a pre-emptive email assuaging customers’ concerns. You could also offer a special deal incentivizing them to continue their subscription. And you might then go a step further and target competitors’ customers with the same combination.
Over To You
One of the key elements to creating a great customer experience is building a seamless, non-interruptive journey that consumers follow from the first interaction down to purchase and usage. However, the customer journey is no cakewalk. Ultimately, the only way to truly differentiate your brand experience is through constant improvements driven by data. And without AI, that is a huge ask.
AI is not just making marketers’ and salespeople’s jobs easier but also giving them an incredible competitive advantage by directly influencing customers’ perceptions and providing them with personalized experiences that actually satisfy their needs.
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