NEWS - FEATURED STORY

Good Lead Scoring is Still Just Good Guessing


October 14, 2015
By Special Guest
Carl Landers, SVP and CMO, Conversica

How Artificial Intelligence Can Help You Get to Know Your Customer

Never before have we had access to so much information about our ideal customers and the actions they take on their path to purchase – from email click-throughs, website visits, keywords typed, web pages viewed, and the online content they have downloaded. We often also know their job titles and purchasing power, company types and sizes, their age and their interests, and we can even find out their eye color and shoe size. But with all of this data we’re harvesting, the most important criterion that we haven’t been able to definitively capture is the prospective customer’s actual intent – are they ready to purchase today, are they researching information for a future purchase decision, or are they simply looking for competitive information?

When it comes to contacting a “qualified” potential customer, many companies rely on lead scoring; a methodology used to rank prospects against a scale that represents the perceived value each lead represents to the company. Lead scoring can result in inaccurate and misleading information as it assumes a “lead” is qualified based on a predefined set of demographic, firmographic and behavioral information. But what’s lacking is the gauge of a person’s interest and intent. You’ve gone to all this costly trouble of modeling what should be a good customer, collecting every little bit of personal information to learn about your potential customer, but then stop short of the most important step: actually asking if they’re interested in progressing to a purchase.

Lead scoring can tell you who has interacted most with your website, but not which visitors are ready to buy now. The only way to truly qualify a visitor into a potential customer and determine their purchase intent is to engage them in a conversation via phone or email, which is costly, time-consuming and given the shear amount of leads, sometimes impossible. There is a better way, however to “automating” these initial but important steps in the sales process: queue artificial intelligence-based lead conversion software. Acting as a virtual sales assistant, the software automatically contacts, engages, nurtures and qualifies every prospect by engaging with them in a two-way email conversation. And when the virtual assistant detects purchase intent or desire to engage in the sales process, she immediately alerts a company sales rep to engage.

If you want to nurture a lead, you need to cultivate a personal relationship with them and explore their interest by engaging them through dialogue. Dialogue is not a one-way communication. It is a two-way interaction that involves questions and responses by both parties. Two-way dialogue will help you discover whether a prospect who downloaded three white papers and visited your website four times is a qualified decision-maker or a student conducting research. AI-driven lead conversion software goes beyond lead scoring so you can know the difference before a sales rep contacts them. A persona (or virtual sales assistant) automatically asks a prospect questions in natural two-way email conversations to understand their needs and uncover their intent. This automated approach to humanizing “lead scoring” can be a huge shift in your lead management.  It makes the initial sales process smarter, more human and more efficient - and the results prove it, as some companies have experienced response rates as high as 50% when they engage their prospects using this type of “virtual sales assistant” because prospects respond favorably to a “human” touch.

The new car buying process is a great example. Automotive sales research shows that 48% of salespeople never follow up with an inbound lead. Moreover, 33% of leads who have shown interest are not contacted simply because dealership salespeople are overwhelmed by the volume of incoming leads. An AI-driven virtual sales assistant off-loads the follow-up process from the overworked sales team to identify leads ready to engage in a purchase discussion, as well as leads at risk: previously qualified prospects who say they have not yet been contacted by a sales rep. By automating the early stages of lead follow-up with a virtual sales assistant, the dealership can focus the salespeople on selling rather than chasing leads and can ensure that no potential buyer is ever dropped no matter how long it takes – days, weeks or months.

AI lead conversion software goes beyond lead scoring. Artificial intelligence software can automate early stages in the sales process by humanizing the interaction a prospect has with a company and by linking the information marketing receives with the actions sales reps need to take. The more efficient automated marketing tools become at attracting potential customers, the more relevant AI lead conversion software becomes, as it can quickly, cost-effectively and tirelessly sort through and identity potential customers who are ready to buy.

Carl has over 20 years of B2B marketing experience in high tech. Prior to joining Conversica, Carl was chief marketing officer at Serena Software, a leading provider of software development and deployment solutions to the Global 2000. He joined Serena as VP of product marketing and demand generation after serving in a similar role at CA Technologies in the company's portfolio management business unit. Carl's previous experience includes senior marketing, product management and product development roles at Niku Corporation, Tyco International and Raychem Corporation, and startups Perfect Commerce and Zoho Corporation. Carl holds a Bachelor of Science degree from Stanford University.




Edited by Stefania Viscusi

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