Customer Retention in the World of AI Marketing
Using AI Marketing for Retention
Marketing has undergone a tremendous paradigm shift from the old school ways to the new age of ai and machine learning. Is this really where we're heading? Not only heading but already there. Any successful CMO is most likely already engaged in the latest new comer in Marketing Automation Software, whether be it Marketo, Hubspot, SharpSpring, Act-On, Pardot, Infusionsoft or a host of others in the ever increasing arena of AI Marketing Automation.
Branding, personalization, automatic engagement and auto-responders are important as a new breed of marketeers track the customer experience. Engaged website visitors are assigned a lead score, advanced as an MQL (marketing qualified lead) and after a series of predetermined touch points, are presented to your sales department as an SQL (sales qualified lead) to complete the journey from lead to a customer. What happens after the conversion? How do you market toward existing customers or learn from their profile to ensure they remain part of your customer family?
RETAINING YOUR CUSTOMER AFTER THE SALE
The journey continues after the sale. You have acquired a customer profile after they've gone through several touch points during a campaign strategy. They've filled out a form or two, read a blog/article, watched a video, perhaps viewed a pricing page and at some point purchased a product or service. You've assigned a customer number and they now have history in your database. Many marketing professionals leave these capable customers in the hands of their faithful sales team and perhaps send some email campaigns to them periodically and call it a day. However, the successful marketers will use AI marketing to streamline the gathered data and uncover critical insights and preferences from their existing customer base to create customized campaigns moving forward to generate new sales or referrals or both. The goal here is to decrease the churn rate we talked about in the previous article and increase the CLV (Customer Lifetime Value). Some of the most common retention practices are from some of the biggest players in the industry. Amazon takes user behavior and makes purchase recommendations, Netflix uses a similar method for movie recommendations.
PREDICTIVE ANALYTICS HELPS IN RETENTION
Customer retention can be directly related to customer satisfaction. Engaging in predictive analytics will create a better user experience hence increasing customer satisfaction and retention. Your marketing automation platform is your workflow machine. This allows you to define rules-based actions and ground all your marketing activities. This becomes the center of your campaigns or the tool shed for marketing. However, your tool shed will not answer the question of what you should do next. This stage is where we engage predictive analytics. Spotfire defines predictive analytics as "the use of statistical and machine learning methods on historical data to predict future outcomes. The goal is to use the knowledge of what has happened in the past to predict what might happen in future to seize opportunities and reduce risks."A predictive analytics tool will harness all the data you collected and then combines it with external factors to help determine future marketing initiatives. Lead scoring is the most common of all analytics and built in to most Marketing Automation Software. Predictive Lead Scoring is similar to traditional lead scoring only much more intelligent. Instead of hard and fast scores being assigned for specific categories like -3 if it's not a vertical market lead or +10 because marketing is in the position title, predictive analytics takes thousands of other factors and variables to determine a much more accurate number. The predictive analytics tool can then make suggestions on actions based on many of these external factors like other services the lead has used, talking points, customer's intent. These are all important actionable items that makes it easier for the sales team to sell, service and maintain a strong relationship. Some examples of Predictive Analytics Tools are EversString, AgilOne, Optimove, insightsquared.com.
NOTHING BEATS HUMAN INSTINCT
Keep in mind these are tools. At the heart of all these campaigns is your CMO and team they've built. Use the tools wisely and use creativity and collaboration to bring it all together and your customer will have a personalized experience and high satisfaction rating that will generate more business, more leads and reduce the ever dreaded churn.
Experienced Inside Sales Representative | SolidWorks | Dassault Systemes 3D CAD and Simulation knowledge
6yNicely done Rob!