This week, we’re joined by Justin Norris, Solutions Architect at Perkuto to talk about how his experience with hundreds of Marketo-based sales and marketing stacks has given him a unique perspective on sales automation, lead routing, and architecting solutions that string together many technologies and systems to do awesome things. Justin also chats with the hosts about his thoughts on B2B advertising and why ABM is making outbound cool again.
This article was originally published on the OpenView blog by Sean Zinsmeister, Senior Director of Product Marketing at Infer.
The hype around AI technology is at all-time high, with the market forecasted to reach $37 billion by 2025. In sales and marketing, the potential for 10x conversion rates and accelerated growth from AI-driven predictive analytics is enticing. But what’s really possible and what’s still in the distant future?
Sales and marketing are ranking in the top three markets most heavily affected by the boom in AI investment, according to sources like CB Insights and O’Reilly Media. Industry giants are announcing more AI plays—Salesforce acquiring Metamind and launching Einstein, or Microsoft rolling out Dynamics 365 with AI technologies Cortana, PowerBI, and Azure Machine Learning.
However, there’s a disconnect between what AI can do and what customers and investors expect. Buyers of AI-powered tools aren’t always familiar with the underlying technology, nor do they know which vendors can deliver on promises of accurate and useful predictions.
Predictive Analytics vs Other AI Technology
In sales and marketing, predictive analytics is a type of AI that has gained impressive momentum in recent years. Companies use this technology to predict which leads will become customers based on traits or behavior that indicates their likelihood to buy, then make decisions on how best to pursue those opportunities.
Predictive analytics isn’t the only type of AI used in sales and marketing applications, but it is where a majority of innovation is happening today. Although it’s easy to be enticed by the idea of fully-automated AI workflows or robot virtual assistants that are powered by deep learning and natural language processing (NLP), those technologies aren’t yet ready for implementation on a large scale. Predictive analytics offers tools that work now, making decision-making easier for startup sales and marketing teams who are increasingly inundated with data.
This article was originally published on the Sales Hacker blog by Sean Zinsmeister, VP of Product Marketing at Infer.
Every CEO wants to squeeze more out of their investments in customer acquisition. And that’s particularly true in today’s market. Stock multiples have come down, especially for many business-to-business SaaS companies that are not yet profitable. In this environment it’s all about doing more with less, and hence we’re seeing the rise of the “moneyball” CEO. These smart leaders leverage predictive analytics to grow revenues with what’s already in their pipeline.
Before getting into how to identify this “whitespace” of untapped opportunities, let’s take a step back and think about what executives should be doing to drive revenue. If I were to encapsulate a go-to-market (GTM) manager’s key functions as an algorithm, it would look something like this (in pseudo-code):
Loop Until Fired():
There are fairly established tools for the forecasting step — like Birst, Cloud9, Domo and GoodData — and the reassigning and enabling step is generally covered by proven approaches to training, hiring / firing, territory management, reallocating spend based on customer acquisition costs (CAC), etc. However the step of identifying specific gaps in the pipeline is the toughest to nail (especially when it’s late in the quarter), and it’s the defining the step that separates mediocre from amazing strategic leaders.
It’s time for this second GTM step to have a framework that’s just as repeatable as the other two, and we finally have proven data science to make that possible. Predictive analytics is a great way for any B2B company to mine their business funnel for deals that can close quickly, and identify potential revenue they might be leaving on the table. In fact, I’ve benchmarked several companies and found that they’re consistently sitting on pipeline which could add 10% of overall revenue from leads and contacts they already paid to acquire.
As we move into 2017, we can’t help but take a moment to reflect on everything that our team has accomplished this past year. We’ve released new products, hired new leadership team members, sponsored some incredible industry events, broken company records and so much more.
Here’s a hearty thank you to all of the folks who have not only helped us reach these milestones, but made the journey fun along the way. To our employees, customers and partners — thank you for making the Infer community a vibrant, educational and exceptional group to be a part of. We look forward to exciting new things to come in 2017!
It’s always a pleasure to uncover a new predictive innovator in our customer community, especially when they tell us that they were able to make an impact within just one week of adopting Infer. For example, content management software company DNN saw a 25% jump in its lead-to-opportunity conversions with Infer, along with a 75% jump in conversations to MQLs for its top group of leads. This success was the result of using Infer’s predictive models to find DNN’s highest revenue potential prospects, and gaining clear visibility into which sources and marketing channels generate the very best leads.
We recently had the pleasure of sitting down with Franck Ardourel, DNN’s director of marketing, who elaborated on the impact Infer’s predictive sales and marketing platform has had on his organization:
Additionally, you can download the full snapshot to learn more about how DNN is using Infer Predictive Scoring to:
- Identify the leads most likely to convert to customers.
- Improve sales prioritization, and increase new business opportunity conversion rates.
- Optimize lead gen acquisition programs in order to consistently produce higher quality leads and increase ROI.