The impact of AI on the future of B2B sales is growing exponentially, and as AI overtakes so many conventional efforts in the lead qualification process typically, the step performed by a Sales Development Representative it’s not surprising. With the use of AI SDRs to assume and optimize many lead qualification processes, can AI truly qualify leads more effectively than human intuition, instinct, judgment, and experience? Is it best to allow an AI SDR to handle lead qualification entirely on its own, or can it do its job better with human counterparts?
How Lead Qualification Was Done with Humans
Lead qualification was done with human SDRs. Human SDRs talk to the potential lead and based on seasoned judgment, experience with the product/service and conversations had, they assess and ascribe levels of interest, needs and purchase capabilities. Humans can read emotions and gestures, empathize, build rapport and relationships and gauge quickly if someone will be a good fit for a customer. Yet human lead qualification is inconsistent due to distraction or personality quirks at times and thus, accuracy suffers while time filler activities (meeting follow-ups that weren’t needed, for example) become more commonplace. Sales efficiency suffers.
The AI SDR Process for Lead Qualification
AI SDRs qualify leads with automation based upon predictive analytics, data gathering, and natural language processing. AI assesses a potential lead’s fit, intent, and engagement level through a compilation of historical and real-time data points. An AI-driven sales development representative can manage this entire qualification process at scale, ensuring consistency and speed across vast outreach efforts. AI talks to hundreds, thousands of prospects at once and qualifies them in real-time without the need for breaks that humans require. AI qualification is accurate and consistent, which leads to sales funnel efficiencies.
Speed and Efficiency: What AI Does better than Humans
When it comes to lead qualification, the one thing that AI far surpasses humans in its speed and efficiency. AI SDRs can process new information obtained from multiple conversations simultaneously and determine in real-time whether or not a lead is qualified and respond back to the prospect. This both hastens qualification and reduces response time to keep prospects engaged, but simultaneously gives human SDRs more time for richer back-and-forth conversations that rely on emotional intelligence, creativity, and complex decision making.
AI’s Greater Ability To Qualify
AI SDRs qualify through a more extensive, data-driven reality that eliminates the subjective nature of the human qualifier. AI employs extensive market research, previous purchases, previous outreach attempts and interactions and more to create an accurate picture to determine if someone is a fit for a product or service. Qualifying based on buyer intent seemingly to a T while also being able to replicate outcomes across the board for any intersection with any human SDR ensures that subjectivity does not cloud judgment of fit.
AI’s Lesser Ability To Qualify Because It Lacks Nuance/Human Emotion.
Where AI fails to qualify for suitability is when it lacks nuance, emotion, and context. AI SDRs may not hear tonal inflections or view body language that signals enthusiasm, disengagement, or ulterior motives.
Where sometimes human intervention is still necessary, the ability to go by the book where emotional attachments mean all the difference might qualify someone as a bad fit when in reality, if human qualification happened with merely a more emotional approach, it would be the opposite.
Human SDRs: Empathy and Intuition That AI Can’t Compete With
Human SDRs have an emotional IQ, instinct and people skills that render the qualification process irreplaceable. Human SDRs can establish real relationships in almost no time at all, comprehend what’s being said and how with verbal and nonverbal cues easily, and distinguish whether someone is being truthful and truly interested in making a purchase with great nuance. These people skills help humans qualify prospects appropriately amidst sensitive or dire situations where an AI would fail and keep conversations genuine and empathetic when necessary.
The Ideal of Both Worlds with AI and Human SDRs
Companies are not necessarily looking to have AI SDRs replace the position altogether. Instead, the combination of both forms strengths and achieves the greatest means of lead qualification. For example, AI SDRs can qualify at scale quickly over short periods, they can find out which connections are truly qualified with great precision and they can easily eliminate unqualified contacts with little frustration. On the human SDR side, human SDRs can relate to qualified leads on deeper, more complex understandings and they can use emotional intelligence, creativity, and judgment in the moment to develop genuine relationships where trust is central to the connection.
AI Can Learn and Get Better at Qualifying Over Time
AI SDRs learn and improve over time when it comes to their qualifying abilities. Through patterns and dedications and over time ranking and assessment of data, AI SDRs can change their qualifying parameters based on trends over time after engaging with prospects. Each offering to a prospect provides more information to the AI on how to better accurately gauge the quality and intent of a lead. This feature aids in overall accuracy for qualification while keeping the lead qualifying process fluid, adaptive and highly granular for sales acquisition.
Ethical, Transparent Application of AI in Lead Qualification
AI carries an ethical component as it becomes more utilized for lead qualification. For instance, transparency about utilizing AI to qualify potential leads helps garner trust, for prospects need to understand when they’re interfacing with AI. Thus, organizations that operate ethically for qualification with transparent use cases will be seen as credible with customer trust and possess their ability focused on ethical/honest selling efforts.
Errors Corrected with Human Intervention for Quality Control and Authenticity
Should the AI not understand certain nuances or make mistakes, however, the findings remain that human intervention post-qualification for SDR AI remains necessary. For instance, human SDRs monitor and evaluate AI findings frequently, correcting them and providing feedback to algorithm adjustments so that over time, the AI either stops making mistakes or learns how to adjust to new situations faster. This human intervention is ongoing and ensures that qualified findings are correct and authentic, a balance between what humans easily understand and what machines can accomplish at a much faster rate.
Measuring Effectiveness of AI Qualifying Efforts Over Time
Organizations with the ability to access SDRs through AI should measure effectiveness of SDR qualifying efforts over time. Revenue-based metrics such as qualification percentages, conversion percentages, compliance percentages, time to respond, and Net Promoter Scores indicate how successful the SDR AI qualifying efforts have been over time. If these metrics falter, measurement indicates where strategic holes may lie but also provides opportunities for training and incremental human involvement to correct any shortcomings or deficiencies where AI would need strategic human assessment, access or adjustment.
Human SDRs Trained to Work with AI.
Successful implementation of AI SDRs comes from training the human SDRs, as well, how to best interact with, evaluate and use the results of the AI.
Properly trained, human SDRs will understand how to best toggle between automated operation and human-based adjustment. An educated sales team understands when an AI has adequately qualified a lead, when they should interject and how to best work with an AI qualified lead.
Future Trends: AI and Human SDR Collaboration
The longer this technology progresses, the more nuanced and emotionally intimate subsequent conversations will be; the increasingly finer line differentiating SDRs from AI will become nearly indistinguishable. As AI advances in emotional intelligence, sentiment detection, natural language processing, and contextual comprehension, leads will engage with increasingly SDR-like AI. This will perfect the general accuracy of lead qualification and joint efforts between human SDRs and their robotic friends, paving the way for what proper lead qualification should be.
Can AI Truly Qualify Leads Better than Humans?
The big overarching question remains. Does AI qualify leads better than a human? Yes and no. Yes and no because both AI and human SDRs have relative capabilities on each side with respective strengths that may or may not overlap but never compete. For example, AI has the advantage over humans in processing speed and scale as well as objectivity based on data. AI does its analytics via massive datasets at lightning speed, detecting microscopic patterns and performing tedious tasks with razor precision, free of human faults like fatigue, disinterest, and distraction. When there are thousands of leads to qualify, being able to qualify someone expeditiously on the front end, using a handful of specific data points to classify what a prospect needs speeds up the time to first connection and lead engagement.
Where AI falters, however, where humans flourish; the technical advancements of AI fall short to human listening that consists of empathy, intuition, and discretion. Emotions are not black and white developments; where AI SDRs might view responses in either a positive or negative context, real human SDRs learn emotional inflection and intent, build authentic relationships, and go with the flow should dialogue veer off course. This emotional intelligence encourages a perception that the call is intimate that its humans, in the moment, with human relevance understand what’s at stake for a potential client. Human SDRs sense motivations under the surface, hear objections with understanding or see inflection on their faces as they “get it” what a prospect wants or why they hesitate and these are still difficult for AI to imitate accurately.
Therefore, framing the debate as either qualified by AI or qualified by humans is irrelevant; when each option exists to enhance the sales process, companies will feel more connected. The integration happens, too, as AI can sort and prioritize leads based on metrics in the funnel’s beginning stage. Qualifying at the top based on numbers helps an SDR transition from a numerical-based approach to something more organic, for now, they’ve gotten the data-driven filtered group to which they can rely on emotional awareness and creative skills to connect, clear objections and re-qualify.
Therefore, by combining the purely rational, quantitative elements of AI with human SDRs’ emotional awareness and nuanced, interpersonal decision-making, companies enjoy the best of both worlds for a qualification process that is not only supremely efficient but also compassionate. This blend of energies facilitates unmatched accuracy, engaged prospects, and meaningful outcomes. Accordingly, they not only harness every avenue available to them for successful qualification, but also foster deeper connections for enhanced customer loyalty and differentiation in this increasingly difficult B2B selling space.
Final Thoughts: Embracing the Best of Both Worlds
Ultimately, this AI vs. human SDR discussion overlooks one critical factor: one isn’t necessarily better than the other to the point where the League qualifications process is taken away from either side. Still, the idea is to leverage both where applicable for efficiency and effectiveness. Companies best positioned to understand and leverage the advantages of each will ensure their long-term success in providing effective, nuanced, and comprehensive sales solutions for their prospects; for example, the advantage of AI is a data-driven advantage in formatted actions that can be repeated and scaled. Conducted at high speed with consistency in mind during the initial stages of lead qualification, for example, can allow AI to sort through thousands of prospects quickly and efficiently to determine which prospects will be most likely to convert at the top of the funnel.
Companies willing and able to operate in such a paradigm have a competitive edge over those who cannot, constantly offering positive sales experiences that provide information to prospects, engage them, and give them a reason to convert sooner rather than later. In addition, with the competitive edge of learning from exposure to human traits, the ability for AI AND humans to trade feedback creates an atmosphere of continuous learning; for example, human SDRs can use their contextual feedback components to make AI’s algorithmic abilities even more human; AI’s assessments give the human branch the analytics needed to make better choices and more targeted outreach down the line.
Ultimately, in a B2B sales arena increasingly muddied and competitive by the day, those organizations that can appropriately adjust to this equilibrium of AI efficiency and human empathy not only improve their lead qualification accuracy but also foster more intimate relationships with clients for extended periods of time. The awareness that both AI and humans have specific traits that they individually bring to the qualification process on a continual basis means that companies will achieve sustainable results from sales endeavors for a consistently better image, effectiveness, and expansion over time.
About The Author
