How to Scale your CX/CS with AI
Nov 13, 2023
As an AI company, Syncly brings various use cases to teams in different stages. Nevertheless, there is one core value that benefits all users as they look to adopt AI for a full workflow transformation—scalability. AI provides the best ROI for organizations leveraging AI to replace workflow that is labor intensive, but essential—types of work that need both precision and speed that requires more resources as company grows. When current workflow is no longer sustainable and scalable, that’s when you get the instant value by implementing AI.
For example, tagging and categorizing customer feedback by the nature of the feedback, or by product/service area demands never ending onboarding for new team members and also on the knowledge of new products. Maintaining the current level of customer visibility requires more resources at the growth rate of your customer feedback.
AI dramatically reduces this cost of data visibility while you can enjoy all the upsides including;
You can finally rally your organization around the same goal based on unfiltered and unbiased data.
Engineering resources are deployed to the most important tasks first.
You can easily validate your action by analyzing the feedback trend.
You can also capture why customers are leaving your platform, and plan your next launch to prevent it.
You can build features targeting specific customer group, or specific use case.
With leaders from both enterprise and startup world, we were able to get an inside look about how they are leveraging AI to scale their business and the CX/CS team. Here are key takeaways;
PLG motion and AI
Kian, CX leader at Tome
Benefits of PLG
PLG makes your business scalable by enabling a quick adoption especially if you are a productivity tool. PLG motion allows you to have so many champions. So when it comes to a company making a buying decision, there's a lot less pushback and obstacles. To successfully implement a use of any new tools, you need to have folks that are excited about using it. It's very hard to do that without having a true PLG motion.
Sandra Ex-CS leader at Autodesk
Scaling through Automation
Successfully scaling a customer experience team involves strategically automating certain part of the customer journey while maintaining closer human touch at some level as well. As one of the key initiatives, I introduced a premium subscription model and it provided a self service model to manage users licenses and usage insights for all the mid market customers, which could never existed before.
Sandy, Ex-CS leader at Oracle
Enterprise Scaling Through CLG
Product-led growth (PLG) and Customer-led growth (CLG) are both important strategies when scaling to the enterprise. CLG motion revolves around personalized interactions, initiated by a thorough understanding of the customer journey. Leveraging multiple data sources, weare able to have the insights to focus on the customer's needs and friction points, in order to have a deeper understanding of the customer journey. A key scaling strategy involves personalization by tailoring automation methods based on how customers prefer to interact, including options like Chatbots, knowledge centers, and community-building. In addition, there are cost-effective initiatives like customer office hours and recorded help videos, all grounded in a genuine understanding of the customers’ pain points.
CX/CS of the future: How to leverage AI to scale your team
Are you using any AI tool or looking for an AI tool to help you do that?
We leverage data analysis and tools like Intercom to streamline daily tasks, enabling organizations to maintain high productivity. More we supercharge everyone with these productivity tools, each member of the team stays productive at work. Now teams don’t have to scale at a rate that matches the volume growth of the customer base. This helps startups stay nimble and could ultimately extend runways.
Datas like CSAT and NPS are often a lagging indicator versus real-time analysis. Real-time data analysis to navigate subjective customer feedback, is definitely an area of application that I'm looking for today in a leadership role.
There's a lot of room for error to process a large number of data if done so manually by a person. I think that's a great application for an AI automation. Even for big corporates, AI models that personalizes and provides insights automatically would certainly be a value.
AI has brought customers that were never interested in the tools of early stage startups. There are more early adopters than ever. Is this a phenomenon you are seeing and how does it benefit companies?
AI reshaping the target persona
Six or seven years ago, we would all go to Google and ask a question at home expecting to get an answer right away. However, many of us weren’t able to get quality outcome because we would have to be really good at structuring our questions in certain ways.
Introduction of AI enables people to talk to machines in their own language and getting high quality outputs. This allows users to feel like the software became much more intuitive. I think that removes the barrier from setting up a tool, opening doors to 16 year olds who’s used to all the apps on their phons to uncles who have not used any software before. This phenomenon is great. However, it makes it tough for CX at the same time. Because now all of a sudden, you don't have your typical early adopters who are willing to give you some time to upgrade your product. Another challenge is what I call an AI tourism.
Do you think these new wave of free users can become a legitimate pipeline for companies, and eventually convert them into paying users?
Absolutely. So you look at tools like Grammarly, and they've been using AI for ages now. What they focus on is a consolidation phase. Let’s say you get a user who buys a license on their corporate credit card. And it turns out there are 20 other licenses on the corporate credit cards. At some point, someone in finance comes knocking on your door asking for a better deal on a corporate level. What I believe is really instrumental for companies that are selling into large enterprises to find a way to keep a pulse on these growing user groups, and then come up with a sales strategy to help consolidate that and create a win-win situation for both parties. So it is important to identify when your customers will reach a tipping point when it makes sense to approach them.
Customer conversion is really important regardless of the stage of a company. I think the best thing you can do to increase customer conversion is to follow the success metrics. Use AI tools like Syncly to help you understand based on support data and customer feedback data. Who are the customer cohorts that have converted? Success leaves clues. So all of those clues can help you convert the new wave of customers.
If AI could please take one part of my job, it would be…
Making sense of customer feedback efficiently to allow more time for customer interactions.
Solving contract-related problems, especially in reconciling different licenses.
Using Syncly and providing data-driven insights when introducing new tools.