Welcome to the AI Spring: How Predictive Will Permeate the Software Industry

AI-Spring-1LinkedIn’s entry into predictive analytics has sparked an important conversation, both regarding the state of the emerging predictive industry and LinkedIn’s place in the enterprise software world. Given many of the company’s moves – most notably its Bizo and Fliptop acquisitions – it is becoming increasingly clear that LinkedIn intends to be much more than just an online “professional network.” There’s little doubt that it wants its place in the B2B sales and marketing software stack.

The question is, what does this mean for the other big players? LinkedIn’s latest announcement was very likely the first of many moves that we’ll see in the predictive market from folks like Salesforce, Microsoft, Oracle, Marketo, HubSpot and others. In fact, Marc Benioff recently spoke with Fortune Magazine about the ‘AI (artificial intelligence) spring’ saying, “When I look at the next set of technologies that we have to build in Salesforce, it’s all data-science-based technology. We don’t need more cloud. We don’t need more mobile. We don’t need more social. We need more data science.”

If you look at how the AI spring is likely to play out, there are a few logical approaches the big software players will take as they look to bring predictive capabilities into their product portfolios.

Adding Predictive Features
The first of these is to extend their existing apps with basic predictive functions – essentially playing it safe. These predictive features will probably be based on data the vendor already controls and should work with minimal customization. For example, rather than requiring manually assigned point values to arrive at basic lead scores, marketing automation vendors might enhance their lead scoring capabilities by using a handful of variables that are consistent across their customers to start calculating predictive scores.

How to Calculate the ROI of Predictive Lead Scoring

With content marketing, freemium products, and list-buys, marketers are generating more leads than ever before — but only a fraction of them are good prospects. Predictive scoring solutions like Infer help filter out the noise by programmatically researching every lead and identifying high-potential MQLs. That not only saves sales reps time, but just as important, it gives you an objective way to measure lead quality.

We’re continuously documenting best practices in order to provide a framework for measuring the ROI of a predictive scoring initiative. One approach that lends a lot of clarity to this process is to look at three simple metrics — your number of sales reps, your average cost per rep, and your percentage of bad leads. With this information, you can quantify the cost of wasting effort on bad leads.

ROI_01However, cost savings is only one way to measure the impact of predictive scoring. Most companies want to quantify the top-line impact as well. By looking at your average leads per month, conversation rate and revenue per opportunity, you can understand the potential revenue increase you’re likely to see from predictive scoring.

ROI_02To help you justify an investment in predictive lead scoring, we’re excited to introduce our new Predictive ROI Calculator. This new tool will allow you to plug in these few figures and instantly see the impact predictive scoring could have on your business.

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The Game-Changing Potential of Predictive Analytics

Jeremy is Director of Marketing at Ambition, friend of Infer and guest blogger.

For sales professionals, time and money are one in the same. Ask any successful sales organization, and they’ll tell you that efficiency is the ultimate ally of a good sales process.

Matt Heinz preaches it. Lori Richardson preaches it. Dionne Mischler preaches it. Just yesterday, I spent a solid hour speaking with a Sr. Account Executive for an Enterprise SaaS company. The topic: Sales process adjustments his company made to increase efficiency, which cut his average sales cycle length in half.

Bottom line: If you’re not aggressively pursuing greater efficiency in your sales organization, here in 2015, you’re falling behind the curve and placing yourself at a disadvantage.

Infer Named a “Cool Vendor” by Gartner

Predictive Leader Powers Smarter Sales and Marketing by Pinpointing Buying Signals

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Infer Inc., a leading provider of predictive applications that help companies win more customers, today announced it has been included in Gartner Inc.’s list of “Cool Vendors” in the “Cool Vendors in Tech Go-to-Market, 2015[i]” report. Vendors selected for this report are considered innovative, impactful and intriguing in providing applications that optimize technology marketing, sales or channel management.

Infer’s New Behavior Scoring Predicts Imminent Buyers with Unprecedented Accuracy

Press Release: New Relic Boosts Win Rates by Using Infer to Model Nearly 10 Million Monthly Marketing Automation Signals and Uncover Prospects Who Will Convert within Three Weeks

Infer Inc., a leading provider of predictive applications that help companies win more customers, today announced the general availability of its behavior scoring solution, which helps sales and marketing teams predict which prospects will convert in the next three weeks. Infer is the first company to extensively mine the full spectrum of detailed activity data that is summarized in marketing automation platforms, and use advanced machine learning and predictive analytics to produce highly accurate behavior scores. Already delivering results for several rapidly growing businesses like AdRoll, Chef and New Relic, Infer has generated over 30 million behavior scores for New Relic alone by modeling 47 million activity records.

Take a Listen to “Moneyball for Marketing”

This week our CRO, Jim Herbold, got a chance to sit down with B2B marketing thought leader, Glenn Gow, for his popular Moneyball for Marketing podcast.

Jim Herbold

Jim and Glenn talked about all things predictive – including marketing use cases for predictive intelligence, real world success stories, and four B2B barriers to predictive analytics adoption that are rapidly disappearing. Check out this excerpt from their lively discussion…

Glenn: Tell us an example of what companies are doing in the real world and how they’re taking advantage of predictive analytics.

Jim: Well, there’s an easy example I can speak to. I was the first customer of this company Infer when I worked at Box. When I was running sales at Box, I had the luxurious challenge of dealing with very large lead flows. We had a freemium aspect to the business. We also had a very vibrant free trial aspect to allowing people to get into our service pretty quickly. So, very large flows and leads, we’re talking tens of thousands and I could never afford to apply a lead qualifier to plow through all of those leads systematically over time. I needed a way to find the proverbial needle in a haystack and I started working with Infer.

Infer Helps Leading B2B Companies Accelerate Expansion into New Markets Using Predictive Analytics

Press Release: Companies Like Brightcove, Atlassian and Optimizely Leverage Infer Models to Predict Winning Customers across Multiple Regions, Products and Industries

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Infer Inc., a leading provider of predictive applications that help companies win more customers, today announced that businesses such as Brightcove, Atlassian and Optimizely have used Infer’s “Lenses” solution to successfully accelerate expansion into new geographies, industries and products. Infer Lenses extrapolate market-specific predictive scores from existing Infer models, providing a faster and more accurate way for a company to identify top prospects in new markets.

“We’ve worked with countless companies from early stage to IPO and beyond, and have seen how they’ve expanded into new markets to grow their business,” said Vik Singh, co-founder and CEO at Infer. “With Infer Lenses, we leverage all of a company’s great learnings from other markets and tune their predictive scores so they are useful and actionable for a new region or industry, even if there’s no customer data there yet. This unique service is a huge breakthrough in helping companies scale, and it’s something Infer uniquely provides.”

Where are You on the Path to Predictive?

Going into 2015, experts agree that predictive analytics will provide differentiation to companies in increasingly competitive markets. Now that these tools are readily available to businesses of all sizes, salespeople and marketers need to make the leap from being simply data-driven to being fully predictive-driven. So, where are you on this path?

As any organization grows, it naturally progresses towards greater data sophistication, which increases the efficiency at which you can operate. In sales and marketing, we typically see five levels of customer relationship management (CRM) and marketing automation (MA) maturity, and at each stage customer insight grows and automation increases:

Predictive Intelligence

The Rise of the B2B Predictive Marketer

Marketers have always been a curious bunch. Since Nielsen started conducting formalized surveys in the 1920s, there has been a long history of consumer-based market research that helped explain buyer personas, identify propensities to purchase, and explore the psychology behind the overall journey. Much later, and driven by the advent of the web, companies like Amazon, Target, Netflix, and Google took advantage of the explosion in new data-points to create robust recommendation engines using predictive analytics. The idea was to use statistical models examining historical behaviors to anticipate possible future actions. So if Pandora can suggest which musical artists a user is likely to enjoy based on listening patterns, why is the equivalent in B2B sales and marketing only coming into recent fruition?

PredictiveMarketer