· B2B enterprises are leveraging the power of disruptive technologies such as AI, ML, Cloud, and Big Data for enhanced customer experiences throughout the customer lifecycle
· The overlying goal is to simplify complex support ecosystems, coordinate different functions, and automate repetitive processes
· Robust data mining and architecture is being heavily invested in to not only gain insights, but also improve employee productivity
· B2B companies are pulling out all stops through omnichannel service, chatbots, CRM platforms, and automated escalation management, ticket allocation, and engineer alignment for faster resolution times.
There has been a shift in power from the hands of business providers to that of the customer in the past decade, and recent advancements in technology have accelerated this shift significantly. According to Salesforce, about 67% of individual consumers and 74% of business buyers are ready to pay more for a great customer experience.Nasscom estimates also indicate that the IT & BPM market in India was worth $154 billion in 2017. India is therefore not only transforming its customer experience processes, but we are also providing world-class customer experience strategies for others as well. This is due to the fact that in this digital age, customers are beyond a mere ‘consumer of a product or a service.’ Each customer is studied like a book today, where disruptive technologies help businesses read between the lines through the critical data gained.
Thus, B2B enterprises across the world are investing heavily comprising multi-million-dollar projects in transformative new-age technologies such as AI, machine learning, Cloud, intelligent automation etc. This enables them to handle B2B customer service complexities through insights and coordinated or even automated customer service processes. In other words, they help attain operational intelligence and excellence in servicing other businesses throughout the customer lifecycle.
According to Zendesk, about 66% of B2B customers have stopped buying from a company following a bad service interaction. To avoid this, businesses are using disruptive technology to simplify complex support ecosystems, coordinate different functions, and automate repetitive processes. The first step in this direction is placing robust data mining and architecture in place. For instance, some companies have a digital technical assistance centre for AI-based support operations. Data is mined in these centers from all available sources of information such as calls and logs, CRM tools, emails, chat transcripts, etc.
Enterprises are also using AI to automatically segregate incoming queries or complaints in clusters. Text mining and machine learning helps bucket these support areas in a more definitive manner for easy identification of support routes. The clusters enable engineers to offer contextual recommendations for customer issues while guiding resolutions.
Such an analytical approach helps allocation of the most suitable customer support agent according to their skills and success rate related to a particular cluster. For instance, some agents may be adept at solving security issues while others at order management. This best service engineer recommendation resolves issues faster by collating related cases and knowledge base. Chatbots and other software technologies are enabling self-service and automation of support tasks for L1 tickets, while other more complex tickets are distributed to agents. This raises the question of the channel of customer service.
Omnichannel approaches have emerged in B2B customer service, especially in a hyper competitive market. These multiple channels include email, web, voice call, SMS, and WhatsApp, etc. This is where the technology framework and architecture come in again to centralize the tickets from all sources within one system. The customer support agent is given full visibility to answer more inquiries more efficiently.
It is also important to engage customers in a way that provides them with a better experience. Some companies wrongly assume that bombarding them with promotional emails, push notifications and SMS will keep them engaged. It is possible to achieve genuine customer engagement with the right usage of technology.
Visually appealing website landing pages, helpful product displays, reviews, systematic and personalized push notifications and emails, etc. can help create a much-evolved customer experience. Through data analytics tools, companies are able to find and create ‘customer persona’ as discussed above. By communicating to them about offers, services and new products in their areas of interest will drive more users to the business. The key to increased customer satisfaction is to maintain a steady and personalized interaction. It has been found that loyal customers are seven times more likely to respond to a special offer and five times likelier to purchase the product compared to a casual visitor.
Investing and integrating transformative technology solves several purposes – helps in faster resolution of issues, ticket allocations, ensures engineer productivity, and accuracy in estimating cases. Technology eases operations and proves cost-efficient in the long run by significantly reducing operational costs.
Each B2B industry player must not only understand the critical importance of disruptive technologies, but also the practical competencies offered for enhanced customer experiences. The investments made by companies across the globe have been proven to reap dividends corresponding to enhanced core business impact as well.
Time is of the essence in businesses, both short and long term. While disruptive B2B technologies can ensure saving of time with simultaneous injection of enhanced revenue, those failing to adapt with the current business environment are likely to be left behind. There is a need for a turnaround for such businesses and they must slowly start integrating disruptive technologies in some form or the other. It will all fall in place, once the ball gets rolling, but the onus lies on industry players to overcome the inertia before anything else.
This post has been written by our Guest Sales Author Prasenjit Roy (SVP & CMO@NTT Com) for Relatas.com (Sales AI). If you wish to share your Sales Stories with others, please write to us for access: firstname.lastname@example.org
Relatas is the Sales AI platform that successful B2B sales teams use for Accurate Sales Forecasting using Relationship Intelligence and AI. Relatas helps Sales Professionals sell better and faster, with NO-DATA-ENTRY & helping Sales Managers reduce revenue loss and better sales forecasting.