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HomeThought LeadershipCX Trends and Predictions for 2022: Mary Poppen | Opinion

CX Trends and Predictions for 2022: Mary Poppen | Opinion

Customer experience is a topic that has been discussed by many in the SaaS industry for years. In recent years, it has grown in recognition in other sectors and continues to gain momentum as a critical business strategy.

Customer experience is not just a concept or a team in one part of the organization but a true strategy related to delivering value and outcomes for your customers that translate into growth for your business. Customer-centric organizations are winning in the market by a substantial amount over competitors.

These companies recognize that customer success and experience aren’t just being there when customers need you, but it’s also anticipating their unique needs and developing strategies to help them succeed.

This article discusses how customer success and experience will evolve over the next several years based on our predictions. We have identified 5 trends that are shaping customer experience priorities in 2022, which will continue to evolve and transform the meaning of customer centricity into the future.

Customer Success/Experience will shift from a cost center to a revenue growth engine.

With the adoption of new technologies such as Machine Learning (ML) and Artificial Intelligence (AI), it is time to focus on more than just retention of existing customers. Companies need vehicles to engage customers and help them drive value throughout their customer lifecycle. 

Customer success and experience will be recognized as the company’s growth engine, and Go-To-Market leaders, including sales, cs, marketing, and operations, will have a seat at the Boardroom table. All leaders will have more customer intelligence related to specific business outcomes, revenue retention, and growth and will be able to direct company strategy with more objective data than ever before.

Customer Intelligence will be a priority for C-suite executives and the entire business.

Customer Intelligence is the aggregate view of all customer data, quantitative and qualitative, leading to the identification of patterns in customer behavior that allow for predictions of outcomes. Add the power of Artificial Intelligence (AI), and you’ve got dynamic indicators that allow for recommended action to impact outcomes positively.

With so much customer data and information now available, there needs to be an automated way to analyze the data for patterns and predictions to help target overall, and individual customer needs to maximize customer value. Customer Intelligence powered by AI will be the key to true customer-centric organizations. It will reduce the need to stand up a data science team, reduce the effort of operations teams, and help all business functions prioritize action to maximize revenue retention, growth, and innovation.

Segmentation of delivery approaches will be different from sales segmentation to create a more personalized experience for customers and drive scale and profitability internally.  

The lack of specific post-sale customer data, with Sales being the highest priority function in companies for years, has led to post-sale teams using sales segmentation of customers by default. Pre- and post-sale teams are typically aligned to sales segmentation. It may have appeared that optimization and efficiency were at play by aligning all data and customer treatment to the size of the customer contract value. However, upon closer inspection of customer behavior post-sale, you may just find more unique patterns than you would have thought.

The most optimal customer delivery produces amazing experiences and value for customers. This means you are aligning the delivery to their unique needs and requirements. The contract value and size of the company do not directly equate to the complexity of the organization nor maturity of business processes. Your products and/or services may be spot on for certain customers yet miss the mark for others. Best practices are found not to be so “best practice” for some after all. 

By using AI to analyze the complete customer picture and all behaviors and actions post-sale, you can gain a view that may well indicate that post-sale segmentation looks nothing like pre-sales. In fact, you may just find that you can gain significant efficiencies from aligning your customers by different segmentation criteria such as type of business model, revenue recognition practices, products purchased, etc. Doing this will allow you to align your delivery teams in a way that brings more specific value to customers based on their unique needs vs. simply the size of the company and/or contract value.

Automation workflows will be smarter based on AI to deliver more relevant content and support to customers.

CS Operations has done outstanding work in building workflows that help with scale and efficiency in customer delivery. CSM bandwidth is freed up to be more strategic with customers and to take on more customers to deliver a broader impact. However, CS Operations must define these processes manually and build them into CRM or CSM systems. This assumes the workflows contain all of the right steps to drive an amazing customer experience and that maximum efficiency has been achieved for customer delivery teams. 

Building automated workflows across the customer lifecycle using AI to determine specific customer needs at specific times throughout the journey ensures customers receive the right information at the right time to be successful. It will drive more personalized experiences and outcomes. It will also free CSMs and other account team members to engage more strategically with customers, elevating employee engagement and their success.

Prediction will be the most important driver of differentiated customer experience and outcomes.

Have you ever tried to predict what customers will need? It’s kind of fun to think about it and use whatever data you can find to tell a story of what’s coming next!

However, if you’re like many of us, you haven’t had a full picture of your customers’ behaviors, decisions, and actions to tell the whole story. So while you can predict some specific actions to take, a holistic, prioritized view has been challenging.

Until now! With unified customer data, AI and ML, you can leverage Customer Intelligence to predict what customers will need… and not just around one topic or for the next 3 months, but across many topics and for years to come!

Technology advances have finally made the lives of those in customer-facing roles easier. The days of painstaking efforts and hours to uncover small nuggets of customer value and best next actions are over! 

Customer Intelligence allows you to gauge patterns in customer behavior in real-time and across multiple channels so you can predict upcoming needs to bring maximum value and results. When adding personalization and customer intimacy, you can simultaneously unlock both the technical and data-driven predictions with the specific customer context. As a result, you can become a hero to your customers. You will bring value in a way your competitors can’t, and that creates even deeper relationships and longer-lasting partnerships…the “value/relationship loop!”

In Conclusion

2022 will definitely be the year of Customer Intelligence, and I’m excited to see how customers will become the growth engine for the most successful companies!

Please keep in touch and let me know your thoughts and stories related to the future of customer success and experience in the comment section!

About the author

Mary Poppen
Mary Poppen
Seasoned post-sales leader with experience building and scaling Services, Success, Education, Operations, Support, and Renewal/Expansion teams. Mary has a strong track record building high-performing teams,accelerating revenue, increasing customer retention and improving operating efficiency in high-growth and high-change environments. Her teams have delivered some of the highest customer retention and satisfaction levels in the SaaS industry. She is well-known for her thought leadership in customer success and experience; she often speaks at global conferences, authors content for various publications, and is frequently featured in podcasts. Mary has experience building post-sales teams and processes for early startups including SuccessFactors and Glint, as well as large organizations including SAP and LinkedIn. She is passionate about fostering “people success,” which she describes as the intersection of employee and customer success.


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