History of Customer Success Manager Role
Today, the buzz is all about Digital Transformation. When companies discuss Digital Transformation, they are usually talking about projects that involve complete change in existing business models and involve multiple technologies including Cloud Computing, Big Data, Artificial Intelligence, Internet of Things, Agile, Security, Blockchain and legacy systems. Before explaining how Customer Success Management organisations are key to achieving Digital Transformation, let us look at the history.
Customer Success Roles Origin is in CRM
In 1996, Vantive, a CRM company, created the idea of a Customer Success Manager with a simple idea of asking clients a question: “How are you going to define success?” and “What do you expect from us?” Additionally, the Customer Success Manager was compensated based on the success. In 2004, Siebel, another CRM company, realized that customers getting the most value out of their application were less likely to churn. They created a team with post sale responsibility of increasing customers usage of applications. And in 2005, after SalesForce experienced a very high churn rate, they built the largest Customer Success department in the industry designed specifically to address customer retention and increasing user adoption.
As you can see, there was a focus on the customer experience. Before I go into why the Customer Success Manager role is rising, let us add some context on what how Digital Tranformation projects differ from the commonplace automation projects over the last decade.
More History: Business Process Automation Preceded Digital Transformation
Businesses have invested in technology projects to wring productivity out of their workforce. Productivity increases were gained by taking rules based work, documenting it and turning it into a form of automation. Examples of Automation that have been adopted more widely over the last two decades.
- Automating sales, marketing and/or services using CRM. CRM has largely been democratized over the last decade and has wide adoption
- Automating staff on-boarding (and off-boarding) processes in HR and/or IT systems
- Document management approval and retrieval processes. Any company that has compliance, quality or high risk scenarios have put this in place.
- Expense claims and their approval and payment processing
- Annual leave requests, approvals and integration into tracking system
- Backend financial management and operational processes were automated using ERP systems
- And many more….
Most of these projects were structured around existing relational databases and were performed or driven by a particular Line of Business (LOB).
Digital Transformation and rise of Big Data
Digital Transformation builds on this previous work of automating tasks and business processes. Digital projects go beyond the traditional relational SQL database and are happening across the enterprise. With Digital Transformation, the focus is automating knowledge and analysis (i.e. judgement) type work which is the realm of real-time and behavioral data.
In the past, most data was static in nature. For example, in CRM systems, you may collect names, roles, phone numbers and emails. In HR systems, you may also collect salary, career plan, age and education. Behavior data has been widely used in social media and on-line advertising (e.g. Facebook and Google), but has also been used in commercial settings, especially in utilities sector for managing large power systems (using an early form of Internet of Things). Many companies have embarked on projects to capture and use behavior data for use in risk assessments and targeted advertising. Here are some examples of Behavioral data.
- Network and user anomalies to actively track and monitor for fraud and/or predicting faulty equipment
- monitoring activities that signal or predict client or staff attrition or churn
- hacker or malicious activity such as trying to access confidential data
- weather changes and related impact areas of livestock and crops
- health monitoring either an individual or whole community
- Buying habits, brand preferences, product usage
- Sites visited, apps downloaded, games played
Behavioral data can be from consumers or machines and the capture of the real-time information associated with this is transforming business models.The capture of all this information is partly behind the rise of Big Data, where the volume of data exceeds the capability of existing analysis tools. Perhaps more importantly, making sense of this new data to get ahead of their competition and thereby grow profits is the key to taking advantage of Big Data with Machine Learning.
The Rise of Customer Success Organisations
A 2017 CIO article cited more than 25% of strategic initiatives are still failing, and we are therefore seeing the model of using Customer Success Managers being adopted across the Digital Transformation technology space. With the plethora of activities around Digital Transformation, vendors that sell Big Data, Cloud, Machine Learning and/or IoT solutions are building Customer Success teams to ensure their solution adds value to their clients, thereby reducing churn and growing revenue.
The need Customer Success Manager is broadly needed to help clients navigate the implementation complexities associated with the various projects. The Customer Success manager is a way of providing “skin in the game” to ensure the continued use of their technology by ensuring their clients business goals are aligned with the IT project outcome. Ironically, the purpose of Digital Transformation projects is often to redesign the customer experience. The Customer Success Manager role is therefore designed to ensure this experience is delivered resulting in preventing churn and growing future revenue.
If they are successful in their role, the Customer Success Manager will not only prevent churn, but provide a strong foundation for future products and services.
If you need help with your Customer Success organisation, contact me on LinkedIn.
- The History of Customer Success. See The Customer Success Association.
- For more information on Digital Transformation and an new approach on IoT, see Tom Siebel new company called c3 IoT where he gives a great overview
- For more information on Business process Re-engineering versus Digital Transformation, see James Proctor, Author of Managing Business Chaos. He notes the difference between Rules based work and Knowledge/Judgement based work in his blog
- Example articles on Project Failure include:
- May 2016, CIO magazine quotes that more than 50% of the project managers surveyed reported a project failure.
- August 2017, CIO magazine talks about why IT projects still fail in the age of Agile, DevOps and modern management techniques.