To adapt is to survive. As pandemic pressures accelerated changes in the B2B landscape, even the nimblest operators found themselves under increasing pressure to respond to circumstances far beyond their control, testing data drift detection systems to the limit.
Automated processes went from being a ‘nice-to-have’ to being critical lifelines. And call tracking proved to be instrumental in several disruptive innovations that are reshaping the B2B sales space, ushering in a new era in modern selling.
Read More: SalesTechStar Interview with Jeremey Donovan, Head of Revenue Strategy at Salesloft
Reimagining the B2B Buyer Journey
It’s become increasingly evident that funnel-based approaches to B2B marketing can be unhelpfully reductive. The B2B buying journey isn’t linear.
Buying groups of up to six people are responsible for 79% of B2B purchases. Each of these individuals will bring their own independent experiences, preferences, and research to the table. The process by which these independent viewpoints coalesce into a single preference bears almost no resemblance to the Awareness – Interest – Desire – Action model beloved of marketing schools everywhere.
There’s an increasing shift towards the concept of buyer enablement taking place within B2B marketing. This shifts the focus towards a greater understanding of the way in which buying decisions by consensus are reached, and the role of a sales agent within that process.
Business purchases can be complex. The process by which purchase decisions are reached is best understood as a set of jobs, brilliantly defined by Gartner as follows;
- Problem identification. “We need to do something.”
- Solution exploration. “What’s out there to solve our problem?”
- Requirements building. “What exactly do we need the purchase to do?”
- Supplier selection. “Does this do what we want it to do?”
- Validation. “We think we know the right answer, but we need to be sure.”
- Consensus creation. “We need to get everyone on board.”
In order to complete these tasks, the buying group may need to revisit each task several times, particularly when making a high-value purchase that will significantly disrupt day-to-day operations.
There can be a lot of back and forth. Closer inspection can reveal issues with a favoured solution that causes it to be rejected, restarting the process. Consensus may be hard to reach, requiring additional solutions to be sourced in order to achieve compromise.
Buyer enablement needs to be focused on providing solutions to these problems. And the window of opportunity to assist is small. Research shows an estimated 17% of the time involved in the buying process will be spent consulting potential suppliers (compared with the 27% spent researching solutions online). And the process is likely to involve multiple potential suppliers, reducing that precious contact time still further.
Call tracking is helping us maximise this opportunity to enable the buying group.
Call tracking provides the insights that allow us to map out these complex B2B buying journeys, as they relate to your audience and your product. Combining conversational intelligence capabilities with your CRM and analytics data allows you a greater visualisation of the multiple pain points of any given buying group. How much validation does this team need to reassure them that our solution is effective? How hard is consensus for our target market’s traditional management structure? How realistic are their requirements – is there a knowledge gap that we could proactively help them address? Being able to answer these questions using call tracking and conversational intelligence is helping B2B sales teams reposition, and address buyer needs more effectively.
Read More: SalesTechStar Interview with Jeremey Donovan, Head of Revenue Strategy at Salesloft
We’re also beginning to see call tracking platforms adapting to provide conversational intelligence integration with video call meetings, with tools like Gong and Chorus.AI offering Zoom integration. This is especially relevant when you consider the improved data quality that could be achieved from quantifying sentiment from a group video call.
Revenue Operations
This shift towards buyer enablement is a key feature of what’s known as the revenue operations or ‘RevOps’ approach.
Creating a revenue operations team within your organisation allows you to align the efforts of several different operations. The sales team, marketing team, and customer service team are all repositioned to function within a holistic organisational selling approach. Each team then contributes towards overall goals set by the revenue operations team.
This reduces disconnect between departments and their agendas, eliminates conflict and competition between different departments, and centralises data to provide a solid, unified, inarguable set of metrics. As a result companies become more agile, responding with confidence to a larger number of situations, based on the quality and integrity of their data.
The RevOps approach offers a distinct advantage to digitally-native start-ups – large organisations can struggle to escape legacy sales models, potentially taking years to restructure their processes, their functional silos, and company culture.
RevOps also offers a great way to address flaws in a company’s customer-facing processes. Issues can be identified and remedied across all operations, ensuring that customer trust continues to be built through consistency of response and interaction.
Call tracking offers huge advantages to a revenue operations team. The gathering of call data, with AI interpretation of sentiment, call intent, and outcome, allows RevOps (and C-suite executives) to understand at a glance how closely different departments are working in alignment with buyer enablement objectives.
The immediate availability of this real-time conversational intelligence also enhances response time, improving the overall ability of the organisation to pivot according to fast-moving market requirements.
Addressing the struggle to buy
The urgent need to move B2B sales online in response to the panic was obvious. Some of the practical considerations of making that change were less obvious – with the result that 52% of B2B e-commerce transactions are failing to meet expectations.
In a survey conducted by Sapio Research, 37% of B2B buyers reported order errors, and 32% reported difficulties in finding a suitable product.
Interestingly, 28% reported dissatisfaction at not being able to talk to someone or ask a question.
Adding tracked phone numbers to a B2B e-commerce website ensures customers are supported fully across digital channels, and provides insights into the journey through the website that led to the call. The tracking analytics data then allows the company to identify the best way to answer questions within the content and optimise the website.
B2B buyers are much less likely to complete a buying journey that doesn’t enable the purchase – Avionos’s 2021 B2B Buyer Report revealed that 90% of B2B buyers would turn to a competitor if a supplier’s digital channel couldn’t keep up with their needs. Call tracking helps avoid this unnecessary churn.
Call tracking across multiple locations
Modern call tracking also rose to the specific challenges of the shift to remote working. Earlier iterations of call tracking technology were only feasible to implement at scale, in single locations like call centres.
However, cloud-based data storage has revolutionised call tracking for smaller operations, allowing data from various physical locations and phone lines to be centralised with ease.
This proved invaluable for remote working, with insights and tracking data gained from phone interactions unaffected by the rapid alterations of the physical workspace. The data served an additional purpose in this unprecedented scenario too, allowing agents to continue developing their skillset in their new home working environment using the call sentiment insights. This improved AX, and served to keep agents connected to their organisation, avoiding feelings of isolation and reducing burn-out.
Read More: SalesTechStar Interview with Brian Bartell, Vice President of AI and Machine Learning at Conga