Unfortunately,
practices for qualifying and scoring leads, like BANT, force teams to hand-pick
the wheat from the chaff. Data is analyzed manually, and reps are forced to
apply personal judgment and sporadic research to score leads based on multiple
personas. Not only is this an unrealistic workload, but it also produces
inaccurate and misleading data.
Taking a giant stride toward sales automation, there are
AI tools that can streamline the lead qualifying process with predictive lead
scoring based on accurate data and attributes. Marketing and sales teams can
not only pinpoint but also prioritize which leads to close and nurture in the
future without upping headcount.
Thanks to
predictive lead scoring, Segment, a leader in API integration software, was
able to predict and identify the 16% of its leads that accounted for 80% of its
total revenue all without allocating additional employees or adjusting its
budget.
AI is empowering hyper-personalization.
It's no secret that the modern B2B buyer has become
conditioned to a personalized buying experience. Personalization is no longer a
plus; it has become a mandatory expectation, and AI-powered technology and
software can help B2B businesses meet it.
AI is nurturing pre-and post-sale customer relationships.
According to Drift, Rapid Miner a leading data science
platform provider turned from its chatbot to the AI-powered Lead Bot to help
balance customer support with lead generation.
The bot was able to quickly direct customers to resources
and can resolve many customer inquiries. If it can't, it will pass the complex
issues to the human team for further investigation. This has allowed RapidMiner
to net more than 4,000 leads to date and generates over $1 million in sales.
B2B buyers are beginning to expect the same on-demand
shopping experience found in B2C shopping. AI is bridging that expectation gap.
AI and machine learning are changing B2B marketing.
1. Start with your biggest bottlenecks and problems. Pick
problems that are hindering growth, limiting ROI, or slowing down your
workforce. Take the example of a growing company whose smaller sales and
marketing teams are struggling to qualify, score, prioritize and personalize to
high-quality inbound leads. AI-based automated lead scoring and personalization
tech can boost efficiency and deliver more sales-ready leads without straining
the existing marketing and sales staff.
2. Invest in customer experience and retention. Look for
AI software solutions that can record, analyze, transcribe and infer customer
insights from sales calls with prospects. Teams using such tools can keep their
pulse on competitors in their market and learn how to better engage and retain
their customers.
3. Improve your measurements and analytics. You can
outmaneuver your competitors if you have better data and insights than them.
Look for measurement and sentiment-driven AI technologies that can assist with
prospecting calls and messaging. With knowledge of the emotional reaction to a
pitch or particular style of messaging, both marketers and sales reps can
identify what works and double down on messaging that resonates with their
buyers.
4. Start small. If you're confident that a certain solution can solve existing problems or improve processes, do your research and
look for a vendor with proven case studies or referrals, then gradually test
and monitor performance to gauge a tool's actual potential.
For more info mail us at info@vereigenmedia.com
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