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Elevate B2B customer experience with augmented intelligence

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By Abhishek Bhadra, AVP ( Augmented Intelligence Platforms & Offerings |Genpact) and Pramit Dasgupta (VP Customer experience analytics |Genpact)

The customer experience (CX) is a critical differentiator for all organizations today. CX drives more than two-thirds of customer loyalty, more than brand and price combined. Though organizations are incorporating steps to improve the experience part of a business, a Mckinsey study shows that the B2B CX index ratings are far less than retail customer ratings. Let’s illustrate this statement further.

Suppose you are ordering a product in an eCommerce app. From searching for a product to getting it delivered to your doorstep is a set of seamless processes. Real-time responsiveness of apps has raised the bar for the speed and convenience of doing business in a B2C ecosystem. But in a B2B world, problem assessment to solution onboarding is laden with roadblocks. But you can experience a similar B2C impact in your B2B environment provided your organization has already undergone broader and deeper transformations.

Unique challenges of a B2B ecosystem
The challenges in the B2B world are one-of-a-kind. Let us deep-dive a little. Complex customer journeys The intricacies of B2B customer journeys are significantly more technical, nuanced with diverse product offerings, cross-functional interaction – touchpoint heavy, and tailored to a customer’s business model and needs. Unlike retail customers, the B2B journey experience and operations are typically fragmented by account and region, involving several cross-functional teams.

Lack of a holistic framework
Businesses find it difficult to connect customer behavior and experiences across online and physical touchpoints to important KPIs like revenue, turnover, cost per service, and so on. Only 21% of executives are satisfied with their ability to calculate how CX affects financial indicators.

Muddled survey views
Due to low response rates, survey biases, and limited sample sizes, it is often impossible to ascertain true, statistically accurate drivers of experience across the entire customer base.

Inadequate real-time data-driven insights

Most B2B companies find it challenging to discover, assimilate, organize, integrate, transform, and profile multimodal data of varying volume, velocity, and veracity across legacy and new-age systems. Such data contains valuable insights about the state of their CX and is critical for them to understand and act upon to function effectively.
B2B companies have significantly higher customer acquisition costs. It takes 5-25 times as much investment to acquire a new customer as it does to retain existing ones. Failure to address data issues can negatively impact CX, leading to churn and erosion of customer lifetime value.

Data-led strategies to elevate CX
An obsessive customer-focused strategy can revolutionize CX using the power of data. Here are some pragmatic ways you could explore.

Measure CX minutely
A touchpoint is any interaction (including non-physical interactions) that may influence or alter a customer’s perception of a product, brand, business, or service. Examples of touchpoints in a B2B ecosystem would be – inquiry for a product or service, quotation, order placement, invoicing, post-sales support, and digital engagement. To develop a successful measurement system, one must first create an appropriate framework for computing operational KPIs at each touchpoint and then correlating them with
CX across journeys.

Assimilate data from multi-modal sources: Data-driven insights can uncover critical pain points and discover new opportunities to elevate CX and generate nonlinear growth. For instance, CX data can shed light on customer engagement, churn risk, and customer satisfaction levels by collecting information from individual interactions and feedback. A single data lake can be built at an enterprise level to store structured, semi-structured, and unstructured data about operational metrics and exogenous information that positively correlates with CX.

Predict trends and improve strategic decision making
Predictive data analytics provides insight into future customer buying behavior or probability to attrite. With such insights, businesses can make better product sourcing and inventory management decisions and improve the quality of customer interactions across touchpoints.

Hyper-personalization to improve customer service
Companies should revamp and implement an effective analytics-driven hyper personalization strategy to create differentiated customer impact. It is essential to enhance collaboration across functions to ensure faster fulfillment of customer objectives. You must ramp up resource capability in data, analytics, and CX design to create effective campaign strategies. Defining, mapping, and monitoring incisive customer journeys across touchpoints and business functions can help orchestrate differentiated experience programs.

Augmented intelligence to drive differentiated impact in CX

Once your organization is mature in its data-led journey, it is vital to inject advanced “human in the loop” machine learning (ML) applications to augment business processes and drive differentiated impact. Some of the augmented intelligence use cases, along with a robust data-led strategy, are AI-powered next-best action: Typically, ML algorithms that self-optimize and actuate the inflow of new data can automate deciding your next best move. An efficient feedback mechanism can measure the effectiveness and accuracy of a recommended course of action across your customer journey.

Conversational AI: Advanced customer service AI platforms can integrate with back-end systems like CRM and shipping platforms to provide personalized resolutions to an infinite number of customers at the same time. These integrations can free customer service representatives to focus efforts on high-impact, complex customer situations.

Risk mitigation: ML algorithms can build proactive risk mitigation systems that anticipate and solve issues before they occur. For example, an algorithm might potentially notify a customer about shipping delays caused by weather or proactively inform customers about repurchase dates to avoid possible stockouts.

Benefits of data-led strategies paired with augmented intelligence systems Providing an impeccable CX is as much a science as an art form. Companies that stand out in CX today function in a consumer’s best interest. Some of the key benefits you can expect by re-strategizing your customer focus are:

● Enhanced customer satisfaction
● Higher revenue resulting in improved customer lifetime value
● Reduced cost to serve to lead to a higher profit margin
● Improved cash flow and better working capital

We have much to gain by making data-led strategies and augmented intelligence work in tandem to deliver the right experience. But to zero on the starting point requires careful deliberation.

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