Salesforce for Startups

Enterprise Sales: 5 Best Practices to Convert Leads

I wrote this blog post for the Salesforce for Startups community but thought it applied to our Conversica community, as well. When I wrote this, I attempted to lay out the case for the next wave in sales automation, Artificial Intelligence for Sales prospecting. While AI is not new, with the emergence of machine learning and data science, Marketing AI for customer interaction may usher in the next wave of innovation in the CRM space.

Research shows only 25% of leads are legitimate and should be passed to Sales. So, how do enterprise startups prevent Sales from contacting the wrong prospects?

Technology innovation has transformed lead generation with user-friendly websites, rich content marketing and social selling, but the initial contact with prospects is still heavily reliant on old school, traditional prospecting through phone and email efforts.

Salesforce for StartupsHow do you prevent your sales team from contacting the wrong customer prospects? Prospects who are not interested, not decision-makers or simply individuals conducting their own market research or competitive analysis? Research shows only 25% of leads are legitimate and should be passed to a sales rep. So how do you weed out the other 75% without burning expensive sales resources? The answer lies in having a sales automation system that helps you prospect, follow-up and accurately score your leads.

We know we should touch all leads. We know we should transfer the hot leads directly to Sales, educate the warm leads and get the cold leads into webinars and lead nurturing campaigns. We also know we should split the sales team into sales development (qualifiers) and account executives (closers). But how do we quickly drive more qualified leads into the hands of Sales? I see a lot of companies try to solve the problem with more spend on content marketing and increased frequency of drip campaigns, which increase the inbound marketing lead flow but don’t necessarily boost lead quality. To cope with increased volume, they hire more sales development reps (SDRs) to qualify the leads and find the gems, but doing so drives up acquisition costs and doesn’t increase qualified sales opportunities as fast as expected. Why? Because it’s time consuming and frustrating to get in touch with non-engaged prospects, and we often give up on good leads before we’re able to get the quality of lead engagement desired.

There’s a better way.

The advances in state-of-the-art SFA and marketing automation systems make it easy for Sales to respond quickly with the right content (on-message and with directed calls to action), but the problem is that it still costs time to respond. Time is the commodity that high-growth enterprise startups have in rare supply.

Imagine if we could harness artificial intelligence (AI) with natural language processing for email engagement to add virtual assistance to the initial lead qualification effort. AI could automatically identify who’s really interested, who needs more nurturing and, just as importantly, who’s simply not interested. This would allow Sales to focus their time engaging with prospects who have actually confirmed their desire to be contacted. This transformative approach overcomes traditional sales challenges for companies of all sizes, but is particularly meaningful for lean, high-growth enterprise startups.

Artificial Intelligence for Sales?

In the February 2015 issue of Fortune magazine, Salesforce CEO Marc Benioff states:

“We’re in an AI spring. I think for every company, the revolution in data science will fundamentally change how we run our business because we’re going to have computers aiding us in how we’re interacting with our customers.”

AI for Sales is a combination of sending prospects a smart email with a simple question, understanding the responses with natural language processing and developing a dialogue with the prospect that drives toward a call with Sales.

A few companies have started to develop solutions in this space. My company, Conversica, pioneered AI for Sales over seven years ago. With the experience of processing more than 75M personalized email conversations, we’ve developed five best practices for significantly boosting the conversion rate of leads into sales opportunities. Hint: Automation is key – AI for Sales is even better.

The 5 Best Practices to Convert Leads to Opportunities

1. Treat your leads like real people
Buyers today are bombarded with automated email marketing from companies. Marketers are stuck in a paradigm to send email blast after email blast, hoping for a 1-3% response rate. Buyers perceive many of these emails as spam and specifically create throw-away email accounts to avoid clogging their corporate inbox with marketing. While content marketing and nurturing is still important for education and building awareness, there’s a place for the personalized messages that aren’t marketing or selling, but instead genuinely offer help to prospects. AI for Sales needs to interpret the context of the situation and then send simple messages that elicit a genuine response. For example, your virtual sales assistant says ‘I saw you stopped by our booth, did you get all the information you needed? Would you like to speak with our sales rep?’ and prospects respond, enter a dialogue and ultimately end up with the right sales person.

2. Engage prospects in real-time
You have just spent half your yearly marketing budget on Dreamforce, so you have a lot of sales leads, but a limited sales staff to follow-up with them in a personal and timely manner. Now what? We know 50% of prospects buy from the company who reaches out to them first. How do you compete with the larger companies in your category, who have large-scale telesales organizations? AI for Sales can reach out to prospects in real-time with a personal, genuine and helpful message that elicits much higher response rates because it’s timely, easy to digest and not spam.

3. Don’t give up too early
Sometimes the prospect’s timing is urgent, sometimes the timing is a week or so after the trade show. Sometimes it’s even months later when their purchase window for your solution opens. Following that trade show, AI for Sales would be set-up to reach out to prospects in real-time, then sets a natural cadence to follow up days, weeks and months later until the prospect either responds that they would like to discuss options, or says no thank you. Only 12% of sales people make more than three contact attempts, but 80% of sales are made on the 5th-12th contact. So, giving up too early leaves great prospects behind. We humans are conditioned to stop after “bugging” people a few times, but an AI virtual sales assistant never gets tired and never gets overwhelmed, allowing you to capture the long-tail of leads without adding more qualifiers.

4. Eliminate the grunt work for your SDRs
Does your company struggle to hire and retain great sales development reps (SDRs)? When you calculate the costs associated with this sales group, it is quite high, particularly if you are in one of the U.S. technology hubs (San Francisco, New York, Boston) and if you are an enterprise startup. Additionally, the costs of hiring and training are exacerbated by high employee churn. What SDRs do you know that would like to make a career of being an SDR? The leaders quickly get promoted to an account executive role or get hired away by other companies after you’ve trained them. The laggards get frustrated and opt-out or get let go. The answer to this struggle is to let sales automation – AI for Sales – work on your email leads to determine which are qualified and ready to speak with Sales and which can be returned to Marketing for lead nurturing. This method removes frustrating and fruitless lead qualification workload from your SDRs and allows them to focus on target accounts and high-value prospects, resulting in higher SDR productivity and job satisfaction.

5. Prioritization is paramount
We all know prioritizing leads is critical to sales productivity. With AI for Sales, you benefit from establishing a natural two-way email exchange that results in SDRs getting the useful information they need in order to prioritize follow-up. The prospects perceive they are conversing with a real human and, in trying to be helpful, give out key information about their project, timing and process, when they would like to be contacted and their phone number – we know receiving a direct-dial is a strong indicator of their interest. All of this rich information is automatically logged into the lead record in Salesforce so the SDR can prioritize and have discovery information in-hand to open the dialogue.

Build the bridge from marketing to sales

Lead-to-opportunity conversion is one of the most critical aspects to scaling revenue. This bridge between the marketing cycle and sales cycle is often heated with internal debate as to who is accountable for the lead engagement results. Whether or not you choose to use AI for Sales automation, the above five best practices of prospecting should be followed. I invite you to check out what we’ve developed at Conversica for AI for Sales – a simple to use but sophisticated solution that makes this process data-driven versus human-driven and, as such, radically improves predictability while reducing costs. And, bonus, you might just have less internal debate.

Blade Runner, Space Odyssey, call it what you will…AI for Sales has arrived and it has the ability to transform the way enterprise startups approach sales prospecting.

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