SalesTechStar Interview with Danilo Nikolich, Vice President of Sales, NextRoll

Danilo Nikolich, Vice President of Sales, NextRoll shares more about using AI with a balanced human element to drive faster business impact:

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Welcome to this SalesTechStar chat Danilo, tell us about yourself and your sales journey through the years…

I see myself first and foremost as a practitioner. I think it’s important for a leader to show the willingness and resolve to put themselves out there. This is not for the purpose of proving a point, that a certain approach works, but rather the willingness to learn and adapt when that approach fails. I am also an extremely curious person by nature. Sales is constantly evolving and genuine curiosity drives an insatiable need for knowledge, which, in turn, drives true alignment with your prospects. This is something that I look for when hiring sales development representatives (SDRs) and AEs. Another area I pride myself on is the ability to leave my ego at the door. I have seen environments where SDRs are simply trained on a process, but are not part of creating that process. To my fellow leaders: you probably have SDRs that are in a role (or even their first job) for less than six months and are way smarter than you and can write better emails than you. Get out of your own way and let them shine.

We’d love to hear more about RollWorks new ‘Hot Contacts’ feature and how it enables marketing and sales teams?

Hot Contacts is a way to get the sales team hot leads prior to any form fills. With only 3% of website traffic filling out a form, Hot Contacts help close the gap by enabling the sales team to gain visibility into a large portion of the remaining 97% of the traffic. With average buying committees of 17 people, it allows us to further the sales cycle through a multi-threaded approach. We are no longer limited by one person scoring enough points to become an MQL.

What do you feel sales and marketing need to align on more to qualify sales-ready leads in terms of parameters internally among themselves and to avoid friction when lead handover processes are done?

I believe the issue lies in the question itself. We are conditioned to look for leads that come with preconceived assumptions; they take the form given to them by scoring mechanisms. We use terms like “firmographic,” “technographic” and “behavioral” to justify the value of the lead, but what we are alluding to is a promise of an impending deal. Coupled with this is the concept of a “handover;” I immediately think of an assembly line at a manufacturing facility. Not a bad way to do things if the success rate is nearly 100% (heck I would settle for 50%). The reality is that it’s closer to 5-20%, which in turn leads to a “handover” in the opposite direction (sales to marketing) for the 80-95% of the leads sales that can’t be reached. And the vicious loop starts…

So, if it’s not just about the “lead” and “the handoff,” how should you think about it? Before I move on I want to be clear that the MQL is extremely important. Yet it’s only one signal.

The question is more around what else is there? Here is where it gets interesting. There are a multitude of signals that are aggregated at the account level that allow the sales team to take a thoughtful multithreaded approach. These signals include things like 3rd party intent, known and unknown website visits, ad clicks, engagement with the marketing automation platform (opens/clicks). The list goes on… So it’s less about the MQL and more about an account stage (MQA is the buzz word used for the past couple years) Here is an example of a real life scenario. You reach out to an MQL and make your 7-10+ touches and get no response. As a result, the lead is “recycled” and goes back into the nurture queue to continue to get scored until it pops back up as an MQL. What if you saw an unknown visitor from that company checking out your pricing page, or researching your competition on G2 Crowd. Ask yourself, would your sales team want to reach out to this account? I am sure 90% of you would say yes!

On the topic of a “handover,” I would use the term “overlap” or “cooperation” or “collaboration.” Here is a real-life example of what I mean: SDR team initiates an outbound outreach to a set of high value accounts while the marketing team supports them by building their list of contacts (content syndication) and provides aircover (digital ads). What will this teamwork yield? For our SDR team it helped increase the awareness of who RollWorks is and increased the receptiveness for learning more, for the folks we reached out to. We measured this by looking at the reply rates that involved this teamwork with marketing and saw a 75% increase in reply rates for the SDR outreach. To sum up, think about the account through a multi signal lens instead of just an MQL, and instead of thinking about a smooth handover, think about a collaboration between sales and marketing.

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Can you highlight more about some of the common misconceptions around SQLs and MQLs and what you feel every marketing and sales team should keep in mind regards to this.

Start by taking the politics out of it. I am talking about timing. An MQL typically does not catch this aspect but rather relies on Bottom of the Funnel behavior to make an assumption on timing. That said anyone that is interested in taking a meeting regardless of timing has deal potential. It’s up to sales in many cases to create a compelling case.

The second one is a bit more sensitive and it relates to the effectiveness of your sales process that will ultimately lead to an evaluation of your product or a parting of ways. In either case, it’s not that the lack of an SQL is due to a poor MQL. I would argue an SQL is more a result of work that needs to be done on sales org and not misalignment on expectations with the marketing org around MQL definitions.

A few thoughts on the impact of AI on the future of marketing and sales and how it will further streamline the lead cycle and process in B2B in the future?

It’s exciting to see AI/ML evolve over the last few years. It certainly has its place. Currently it does a great job with tasks like defining an ICP score. It simply ingests the data for your best customers and comes up with an algorithm that can be used to score your prospect list.

BUT, challenges become apparent if your company is young or in an evolving market. Don’t get me wrong, it’s a very important data point to consider, but not one to solely rely on.  Let me give you another example around account scoring. AI/ML can certainly take a look at your data and provide a score.

In some cases, it represented a numerical score like 86 out of 100 or a scale low to high. The problem with these scores is that they do not share any details on “the why,” so the sales reps don’t have any visibility prior to reviewing each account. The human review of the accounts may reveal that an account with a score of 76 was a better target than an account with a score of 90 due to some critical information that AI/ML just threw into a calculation. The risk at that point is that the sales team sees this as false positives and the adoption of the tool tends to drop off. So, while AI/ML do an amazing job in aggregating the data and providing guidance, there needs to be room left for human input and customization in products to supplement them.

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