As predictive analytics comes of age, we’re hearing a lot about data science methodologies like machine learning and data modeling. Until recently, these complex techniques were only employed by a relatively small group of data scientists. But new cloud services for machine learning from the likes of Amazon, Google and Microsoft claim to finally make it easy for any business to take advantage of the predictive revolution. As these types of solutions become common in the market, more do-it-yourself (DIY) tools will emerge for industry-specific flavors of predictive analytics in data-rich sectors like financial services, healthcare or retail, as well as in certain functional areas like predictive sales or marketing.
Press release: New Strategic Partnership Brings Profile Management and Predictive Scoring to Account-Based Marketing
Infer Inc., a leading predictive sales and marketing platform that helps companies win more customers, today announced a Predictive Ad Targeting Platform that helps businesses target their highest-potential accounts and fuel deeper engagement. A new Infer partnership with account-based marketing (ABM) platform Terminus extends the power of predictive analytics to business-to-business advertising. Through this and other partnerships, Infer’s open platform delivers predictive advertising solutions that increase a company’s marketing return-on-investment by leveraging data science to optimize campaigns, targeting and budgets.
Rather than take a spray-and-pray approach or focus only on known accounts, Infer helps companies accurately pinpoint which accounts or leads are most likely to engage with a given campaign, and then leverage this intelligence for greater advertising impact. Infer goes beyond just adding predictive scores into the mix of bidding signals for ad targeting. The company’s platform builds profiles that can encompass both scores and external signals, such as the prospect’s intent or whether their company offers a freemium product.
“Predictive scoring and profiling technologies add tremendous value when it comes to sales and marketing workflows for account or lead prioritization, inbound marketing and demand generation, so it’s a natural extension to bring these advanced techniques into your advertising strategies,” said Vik Singh, co-founder and CEO of Infer. “The most successful approaches are those that combine proven, best-of-breed platforms, as opposed to force fitting a one-size-fits-all solution that applies predictive to both advertising and automation. They are two different sides of the coin, each deserving dedicated focus and depth to do proper justice and to achieve significant gains in marketing and sales. That’s why we developed an open architecture that intelligently feeds our insights into your stack to make CRM, marketing automation and adtech systems all infinitely smarter.”
Building Data-Rich Profiles for Hyper-Segmentation
The Infer Profile Management Platform first combines data that’s trapped in companies’ internal systems with thousands of proprietary third-party signals. It also pulls in valuable buyer intent signals from marketing automation platforms, advertising systems and other data vendors to proactively identify new ‘interested’ accounts to target. Infer intelligently matches, merges, interprets and filters all of these data points so that go-to-market teams can create data-rich, descriptive prospect profiles using a broader range of customer attributes than ever before. Through thoughtful hyper-segmentation of these high-potential profiles, companies can greatly improve effectiveness and efficiency in a variety of sales and marketing programs.
Hyper-Targeting ABM Campaigns for Greater Impact
Infer connects with leading advertising systems to share these carefully defined profiles, and orchestrate whichever actions a company wants to perform on them. For example, by feeding rich Infer Profiles into Terminus, a marketer can show personalized display ads to particular B2B accounts, i.e. best-fit marketers who use the Marketo platform. “Infer’s open architecture makes it simple to take your account-based marketing strategy to the next level,” said Eric Spett, CEO at Terminus. “Companies can pull their ideal customer profiles from Infer into our platform, and effortlessly bring predictive into daily workflows that provide critical ‘air-cover’ for ABM campaigns, and result in faster progressions through every stage of the marketing and sales cycle.”
Measuring Campaign Results through Predictive Scoring
Coming full circle, Infer’s Predictive Ad Targeting Platform can leverage the company’s statistically accurate fit and behavior scoring models for greater predictive power, a deeper level of segmentation, and more insightful campaign measurement. Infer Predictive Scoring helps marketers measure the quality of the leads they are reaching, make course corrections as needed, and ensure that their messaging and channels are effectively aligned with the company’s target profiles.
“Infer’s profiling and scoring technologies, in tandem with ad platforms like AdRoll and Terminus, help us easily employ predictive targeting,” said Alex Acker, senior manager of marketing and insights at Nitro. “By working smarter in this way, we’re able to boost engagement at the top of our funnel, and get a whole lot more for every advertising dollar.”
Infer’s open approach and integrations with other partners like AdRoll, Eloqua, Google Analytics, HubSpot, InsideView, InsightSquared, Marketo, Pardot, Salesforce and Social123 help to make an organization’s existing sales and marketing stack more impactful and effective.
Founded in 2010, Infer delivers a predictive sales and marketing platform that helps companies win more customers. It leverages proven data science to rapidly model the untapped customer profile data sitting in an enterprise, along with thousands of signals from the web, and help drive a company’s growth strategy through valuable predictive workflows. Customers include over 120 high growth companies and large enterprises like AdRoll, Atlassian, Cloudera, Concur, New Relic, Tableau, Xactly and Zendesk. Headquartered in Mountain View, California, Infer is funded by leading investors, including Redpoint Ventures, Andreessen Horowitz, Social+Capital Partnership, Sutter Hill Ventures and Nexus Venture Partners.
Read about Infer’s new partnership on the Infer blog
Press Release: New Predictive Technology Delivers Intelligent Recommendations to Bring Unprecedented Precision to Sales and Marketing Decisions
Infer Inc., a leading provider of predictive technologies that help companies win more customers, today announced its launch of the first predictive prospect management platform for sales and marketing teams. Infer Prospect Management helps companies develop ideal customer profiles and expansion opportunities that unlock value with prospects and customers. The platform leverages artificial intelligence (AI) to make recommendations and trigger actions that help move prospects from one step in their customer journey to the next.
There’s no doubt about it, the predictive space is heating up. And with all the noise out there, it can be difficult to understand what separates one predictive vendor from another. To help navigate the space and see where the technology is headed, we thought it’d be helpful to draw an analogy to the evolution of maps. Today we we’re excited to unveil an interactive page to tell the story. Check it out!
Last week, Elizabeth Dwoskin and Shira Ovide of the Wall Street Journal wrote a great article on predictive sales technologies. Their comparison of Willy Loman from “Death of a Salesman” to modern data-driven salespeople really brings home how much has changed for reps in the world of big data. If you don’t have time to peruse the full story, here are some key excerpts:
“Silicon Valley startups are automating sales departments for a shot at the more than $23 billion companies spend each year on sales software. Some of these startups mine sales staff emails, calendars, social-media feeds as well as news articles and customer databases for patterns that help them predict the likelihood of a sale or the behavior of potential buyers.
Our very own Director of Product Marketing, Sean Zinsmeister, recently sat down with folks from a couple great interview series — MarTech Heads and TA Expert Interviews. During these insightful conversations, Sean spoke with the podcast hosts about predictive sales and marketing, marketing campaign successes and challenges, third-party intent data, the shift from predictive to prescriptive intelligence, his favorite martech tools and tips, and more.
LinkedIn’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.
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.
However, 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.
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.
Press Release: Forward-Looking Businesses Use Infer’s Predictive-Driven Approach to Identify Account Target Lists
Infer Inc., a leading provider of predictive applications that help companies win more customers, today announced the general availability of its account scoring solution. While some companies struggle to sift through huge volumes of incoming leads, others depend on outbound sales and account-based marketing to drive growth. These businesses can use Infer’s new service to source more opportunities by ranking cold accounts based on their fit for the product and their revenue potential – even before making contact with prospects.
“When it comes to predictive scoring, we help companies build the right model or set of models to support their business objectives,” said Vik Singh, co-founder and CEO of Infer. “Infer’s account scoring is yet another way we’re leveraging our experience across a large customer base to help sales and marketing teams find pipeline opportunities with pinpoint precision.”