Every Infer customer we talk with seems to share a new best practice that can benefit the entire sales and marketing community. Most recently, we explored how 20-year-old ShoreTel is infusing predictive insights into its mature demand generation workflows to drive dramatic efficiency improvements. This large telephony and unified communications provider has no shortage of leads, and recognizes that having more people to call isn’t necessarily better. Instead, their demand gen team focuses on working smarter by tightly aligning effort around those activities that deliver the greatest impact for the business.
In a recent conversation with ShoreTel’s head of demand gen (and one of Infer’s Top 25 Predictive Sales and Marketing Innovators), Carolyn Wellsfry Cheng described her company’s demand generation programs, predictive use cases, marketing challenges and cost-per-MQL measurement approach.
Describe your company’s demand gen workflows. Where does predictive fit in?
Similar to any organization doing outbound calling, our market development reps (MDRs) have to prioritize the most important place to spend their time in each moment to get results. Their job is to fully qualify leads as opportunity-ready MQLs (and we go beyond typical industry standards for qualification) before passing them onto the partner and sales teams. I’ve been with ShoreTel for 2½ years, and in that time our team and budget have been fairly flat, but our goals have increased between 20 and 30% year-over-year. All we can do to meet our number is drive efficiency, and we have been successful at that thanks in part to Infer’s predictive sales and marketing platform.
We first segment our leads by explicit action (like “contact sales” requests or white paper downloads) which are prioritized by intent. Meaning if you filled out a contact sales form, our MDRs want to get back to you in minutes. But they might still have dozens of new and follow up leads they have to call each day, and so they use Infer Scores to determine who to focus on in order to reach their individual MQL targets.
That could mean making a few extra calls to someone rated highly, or cherry picking leads from those that might not otherwise get a call right away. They also go back to old lists and use Infer Scores to identify the best-fit leads to revisit. For one area of our business (asset downloads), an MDR would previously have to call 100 leads to get 1 MQL. Infer has helped cut that number down to 12 calls for 1 MQL – a really high conversion off of a large segment with a lower cost of acquisition.
What are the main channels where people are finding out about ShoreTel today?
We don’t have one silver bullet, the truth is we have our hands in a lot of pies across inbound and outbound channels. We do a lot with content syndication. We have a few vendors that run outbound demand generation for us around specific campaigns. We have paid and organic search, display, social, events, reputation marketing, etc. Really we touch everything in our overall integrated marketing plan, and all efforts have to align and lift everything else.
From a demand generation perspective, we’re always looking at what levers we can pull that are going to achieve the right results, because our goals are so aggressive. We have core programs that get us 80% of the way to our number every quarter. Then we have experiments that we’re constantly running, where we’re either trying to optimize something we’re already doing, or adding something new to the mix because someone had a great idea. All of those things fit together and help us achieve our goals.
How do you measure and optimize the success of your marketing programs?
The measurement we’ve been most interested in lately is not necessarily cost-per-lead, but cost-per-MQL. We know that we can source leads, because there are plenty in market and they aren’t hard to find. The problem is, “Are we getting the right quality people who are actually in a buying cycle?” That looks different for every company.
We pick vendors that are willing to experiment with us and try to improve the efficiency of our programs. We just don’t have time or money to call 10,000 leads if zero of them are going to convert to an opportunity. More is not always better, sometimes more is just more. I’d rather my team focus on getting a healthy mix of middle and bottom of the funnel, rather than just looking for the lowest cost-per-lead. That’s why we focus on the cost-per-MQL, as well as things like the freshness of the lead data – i.e. are we sourcing new names or are we talking to the same people over and over again? We also use campaign attribution to see which campaigns and channels are driving the highest growth.
I’ll give you an example. Everybody wants to talk to the IT buyer and we know that IT buyers download a lot of information for a lot of different reasons, but that isn’t always enough of a signal to indicate that they want to buy something – it just means they wanted to read something. I don’t want to spend a lot of time hounding an IT buyer who isn’t actually in the buying cycle. It could alienate them from our brand. We might work with a vendor and ask them to make the form they’re using more prohibitive. We just want to ask really explicit questions around intent, and we only want to see the leads where they say, “Yes, I have a project that I am going to execute in this somewhat reasonable timeframe,” or “I am an influencer in the decision.” Our response rates go up because we are talking to more qualified leads, usually without increasing costs.
How would you characterize ShoreTel’s on-boarding and adoption of predictive scoring?
We started with Infer two years ago, and it has become an important part of our marketing stack. At first, we ran it in stealth for 2 or 3 months, until we could clearly show the MDRs real data. I could say, “Here’s what happened to the Infer A-Leads, here’s what happened to the Bs and here’s what happened to Cs. If you just call the As, you’ll get to your quarterly number faster.” That helped to speed our time to adoption.
We try to be very collaborative with our sales organization, but it takes a little bit of time to get them interested in doing something in a new way. Now, they’re reaching this point where they need more prioritization because they’re getting leads, not only from marketing, but also from channel partners. Some of those are leads that are hot and ready to close right now, while some partners may be sending in colder leads they got at a networking event, but aren’t in market yet. The sales team can’t easily differentiate between the two levels of interest at first glance, so adding Infer to their view gives them one more data point to make decisions.
My way of working is to not push something on sales, but rather to wait until they realize they have that pain, and then show them how we can help them be successful. We were able to go to them and say, “I understand you’re having this problem. By the way, Marketing actually encountered that challenge a year ago, and here is how we solved it. Here’s what we did, here’s how long it’s going to take, you don’t have any heavy lifting, all we need to do is build you a model.” They were very excited to hear that, and it was an easy win for them – they’ve just launched their own pilot with Infer.
Download the full snapshot to learn more about how ShoreTel is using Infer Predictive Scoring to:
- Increase marketing’s contribution to sales by prioritizing the leads that are most likely to convert to customers.
- Boost ShoreTel’s conversion rates and helped drive greater efficiency amongst outbound demand gen reps.
- Optimize marketing programs around cost-per-MQL measurements in order to produce overall higher quality leads.