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SalesPredict Reports 14X Year-Over-Year Revenue Increase

Predictive marketing platform provider SalesPredict announced that the company has seen 14-times increase in revenue compared to the previous year. The revenue growth positions the company to expand its employee base and grow its share of the B2B predictive analytics market.

By using predictive analytics in conjunction with data from CRM and marketing automation system as well as external sources, SalesPredict is designed to help B2B marketers to target more effectively, as well as boost lead qualification and conversion rates.

The company also announced the hiring of Sahil Mansuri as its VP of Strategic Sales. Prior to joining SalesPredict, Mansuri was the VP of Operations at Virool, a native video advertising company.

“We have experienced exponential revenue growth this year and are excited to be able to support our rapidly growing customer base by adding additional staff,” said SalesPredict Co-founder and CEO, YaronZakai-Or. “Our revenue growth shows that smart B2B companies, such as Showpad and Virool, are increasingly recognizing that predictive insights can help them target the most likely buyers, improve their demand gen results, align marketing and sales, and ultimately, drive more revenue.”


Study: 83% Of B2B Companies Say Predictive Tools Having Big Impact

A study conducted by Forrester Research highlights that predictive analytics users are twice as likely to perform well in key business metrics compared to those who use traditional analytics. Specifically, 83% of B2B companies leveraging predictive analytics see "considerable or very high" business impact — noting a higher likelihood to exceed marketing goals, have a higher market share and see annual revenue growth steadily increase.

Liquid Acquires CommandIQ To Enhance Retargeting Capabilities

LiquidLiquid Command IQ, a cross-channel advertising solutions company, has acquired Command IQ, a predictive CRM solutions provider, for an undisclosed fee. The deal intends to bring CommandIQ's marketing automation and retargeting capabilities into the Liquid platform—positioning users to manage advertising initiatives across multiple touch points based on the buyer's behavior.

The acquisition also positions users to leverage their CRM data to target and measure marketing media initiatives. As part of the deal, CommandIQ CEO Noah Jessop will also join Liquid as the company's Head Of Data.

"Our acquisition of CommandIQ supports our overall evolution as a platform and shows our true commitment to offering the best ad products possible to our clients," said Steve Bagdasarian, General Manager for Liquid.

B2B Marketers Flock To Predictive Analytics As Sector’s Promise Fuels Major Growth


B2B marketers are beginning to recognize the power and benefits of predictive marketing analytics and are investing heavily to get up to speed this year. They still have a long road ahead, but early wins by progressive marketers are garnering major attention and spurring demand. Vendors in the space, meanwhile, are registering explosive growth to meet demand.

Forrester Research found that nearly two-thirds (64%) of marketers are implementing or upgrading predictive analytics solutions today or plan to do so in the next 12 months in a report published in July, titled New Technologies Emerge To Help Unearth Buyer Insight From Mountains Of B2B Data.

“There’s a lot of potential in predictive technologies to help marketers engage with prospects and engage with existing customers,” said Laura Ramos, VP and Principal Analyst at Forrester.

Ramos said predictive marketing analytics can help B2B marketers determine when to engage buyers, how to effectively execute cross channel campaigns and where to allocate budget.

A recent study conducted by Demand Gen Report sees similar numbers in its own research. The report shows that sponsored by Lattice Engines, 58% of B2B marketers are either currently use predictive tools or plan to within the next six to 12 months.

“The holy grail of marketing has always been the right message in the right channel at the right time,” said Nipul Chokshi, Head of Product Marketing at Lattice Engines. “Predictive is the piece that gets you there.”

Recent growth and investment strengthens this claim. In the past 60 days, there have been a handful of major cash infusions flowing into predictive analytics providers’ coffers:

  • Radius announced that it scored $50 million in funding that the marketing software company intends to use to scale its predictive marketing platform to meet demand. Radius said in its announcement that its revenue increased by more than 400% in the past year and it has doubled its employee base.
  • Leadspace announced its own infusion of $18 million cash a week after Radius, and the company said earlier this year that it doubled its customer base.
  • 6sense, which raised $20 million in funding in February 2015, received an additional investment from Salesforce Ventures in July that CEO Amanda Kahlow characterized as “significant,” though she would not share exact figures. Kahlow said the investment would enable deeper integration of 6sense’s predictive solution into Salesforce products. 6sense has more than doubled its employee base in 2015, and Q2 revenues this year were four times higher than the first quarter.
  • Lattice Engines raised $28 million in a financing round in June.

B2B Buyers Testing Multiple Predictive Tools

Many of the B2B marketers who are currently experimenting with predictive analytics are using multiple vendors and programs inside their organizations.

“They’re using them to solve problems or doing an internal bake-off to see what works better,” Ramos said, though she acknowledged that gets harder to do in enterprise-level organizations.

Despite the power of predictive analytics tools to lasso Big Data and democratize the process to an extent that even those who are not data scientists can benefit from it, the majority of B2B marketers are still sitting on the sidelines.

“Most B2B marketers aren’t ready to put the full power of predictive analytics into play.” Ramos said. She said in her experience most B2B marketers have yet to drive results beyond advanced lead scoring.

Ramos noted that most B2B marketers have yet to drive results beyond advanced lead scoring. “This view is shortsighted,” Ramos said. “The real value of predictive marketing occurs when you apply this approach across the customer lifecycle.”

Optimizing the entire revenue cycle came was not a priority for B2B marketers polled in the Demand Gen Report study. Even for those already investing in predictive, the focus remains primarily on achieving top-of-the-funnel goals.

Lattice chart 01
Source: “The Full Funnel Effect: How Predictive Drives Value At Every Stage Of The Revenue Cycle,” Demand Gen Report

However, examples of early wins by using predictive abound. According to Lattice Engines, DocuSign used predictive marketing to prioritize leads and run them through a nurturing program. The result was a 38% win rate, Chokshi said. Another client, a financial payments processor, saw a 20% call-to-win rate using predictive. And client VMWare, which used predictive to identify cross-selling opportunities, tripled their win rate.

Kahlow at 6sense said a customer ran a test with 2,000 records, comparing their in-house analysis with 6sense’s predictive technology. Five of the control group prospects converted; 299 of the prospects 6sense analyzed converted. “We’re able to find real results [for our customers],” she said.

For marketers to fully harness the wealth of information available, basic processes and thinking also needs to change, experts noted.

"Predictive should act as the central nervous system powering all sales and marketing."

- Amanda Kahlow, 6sense

“It’s a challenging process,” said David Lewis, CEO of DemandGen International.

Lewis said marketers need to “be careful of the shiny new toy syndrome. Predictive will not solve lead gen,” Lewis said. “That’s going to come down to the people involved and their skill set, and the ability to bring together disparate systems and technology. They also need to master existing technology such as marketing automation and CRM systems.”

“You can have the best lead scoring system and algorithm in the world, but if your sales force is not trained in and using the CRM, it’s a wasted effort,” Lewis noted.

Ramos put it this way: “[B2B marketers] are not thinking holistically about the customer lifecycle to anticipate outcomes. It’s not as easy to make it work as it is to get into it.” She compared it to the early days of marketing automation, in which marketers wanted the technology to be the easy answer.

Therein lies perhaps the biggest challenge, which is changing processes entirely to accommodate the power of predictive marketing.

“These are thoughts and questions that sales and marketing people haven’t had with each other,” Lewis said.

6sense’s Kahlow said that predictive “should act as the central nervous system powering all sales and marketing.”

Ramos also noted that the biggest business impact will happen when marketers learn how to use predictive analytics to simultaneously target markets efficiently, streamline pipeline conversion, retain customers, grow customer lifetime value and turn loyal customers into advocates. In order to do so, Forrester’s Ramos recommends four key preparatory steps for marketers in order “to take the predictive analytics plunge:”

Model ideal account and lead opportunities. To kick off predictive marketing analytics correctly, B2B marketers should sit down with sales, support and service delivery to talk about how ideal customers differ based on their key characteristics (fit), the way they look for solutions (intent), and their interest in what you offer (interest).

Anticipate what success looks like. To use advanced analytics well, you don’t need to start with a hypothesis, but you do need to have an objective to inductively format the question — such as “Which customer is most likely to respond to this offer?” — and let the models and algorithms uncover the patterns in the data that answer the question. Starting with overall company objectives, B2B marketers should look beyond lead scoring to prioritize the list of business questions to tackle with new data analytic approaches.

Work with technology management to size architectural requirements. B2B marketers can’t build advanced analytic systems alone. Developing the business discipline and technology needed to harness insights and consistently turn customer data into action requires close collaboration with your technology management counterparts. Marketing’s job is to define where and how to embed insights discovery in visualization tools or marketing applications — for example, to help industry, product or content marketing managers determine which message or campaign element will connect better with which audience to drive interest, preference and purchase.

Use insight to create more valuable sales conversations. Customers expect salespeople to be experts on their businesses and the market conditions in which they operate. Having insight into account specific issues, and empathy for buyers’ challenges, makes sales conversations more business relevant and welcome. To get there, focus your initial analytics endeavors on helping sales not only pursue the most promising opportunities, but also apply this deeper understanding of their unique client needs to what your brand can promise.


The New Rules of Predictive Analytics: CMO Edition

angela zener radiusThe promise of B2B data is unbridled. Thanks to first- and third-party data sources, marketing teams know more about their prospects and leads than ever before. Predictive analytics tools introduce even more data capabilities for today’s marketing leaders. With the right tools, marketers can discover untapped market opportunities, target audiences with greater precision and predict which prospects will become the best customers.

Marketers have embraced the opportunity, with nearly two-thirds (64%) of business decision-makers implementing or upgrading predictive analytics solutions today or planning to do so in the next 12 months, according to a new report from Forrester’s Laura Ramos. While predictive models offer capabilities to transform insight into action, Forrester cautions CMOs against overly complex solutions.

“Selecting the right solution means you must weigh the relative sophistication of your automation processes and team experience against the level of big data capability you are ready to absorb,” writes Ramos, lead Forrester analyst and author of the report.

As a deluge of new solutions, with varying levels of data capabilities and resource requirements, are now making their way into CMOs’ inboxes, it can be challenging for non-technical marketers to pinpoint the tools and technologies that are best for their organizations. Here are three simple rules to guide the exploration of solutions that exist, regardless of familiarity with data science or statistical expertise.

Rule #1: Don’t Let Complexity Become A Deterrent

For marketers without advanced statistics backgrounds, data science will always be complex and perhaps daunting. While predictive solutions provide the answers to many big data woes, machine learning algorithms come with many complexities and moving parts. To predict real world scenarios, models often incorporate hundreds of variables, a multitude of algorithms, and dozens of first- and third-party data sources.

Given the complexity inherent in big data solutions and required resources to generate usable outputs, how does one exert positive influence over such advanced deep learning and processing? With unlimited computing possibilities, what objectives and capabilities should be executed on first? And most immediate to the topic at hand: what tools should marketers select to enable the outcomes they need?

Ramos encourages marketers to take a step back and master the basics. First focus on solutions that can enhance core, repeatable growth strategies before introducing new, far-stretched capabilities that have the potential to drain resources. She cautions that “despite growing enthusiasm for predictive analytics, technological advancements are outpacing the business' ability to put it to work.” The important thing is not to get overwhelmed or overreach and instead to remain focused on the greater plan and business goals.

Recommendation: Seek out partners who have productized and developed superior front-end processes for what marketers are doing already: customer analytics, market segmentation, campaign planning and sales enablement. Solutions should amplify current marketing efforts and enable the goals that marketers have already established for their organizations.

Rule #2: Think Beyond Lead Optimizations

As Ramos points out, marketers are looking for an edge that can return big results. However, existing solutions — even if combined with vast data sources and other tools — can't deliver the speed and insight required by marketers to achieve explosive growth. The report shows that many other predictive analytics use cases are often only focused on optimizing lead conversions. Often inward or backward looking, these solutions deliver incremental growth at best, and are most susceptible to campaign inertia.

Unfettered by the confines of existing solutions, predictive models better support decision-making and have the potential to vastly improve on both cost and revenue. Even subtle adjustments can multiply reach and profits. Radius, for example, enables companies to discover new customers and markets with predictable and actionable success — insights that enable vastly greater outcomes than simply reiterating on past marketing efforts.

Recommendation: Keep high level goals front of mind when assessing solutions for next-stage growth. Framing the analysis solely in the context of current solutions or marginal upgrades limits the outcomes that can be achieved. Ramos calls this mindset “short-sighted,” saying, “The real value of predictive marketing occurs when marketers apply it across the entire customer life cycle.” The biggest business impact will happen when marketers learn how to use data analytics to simultaneously target markets efficiently, streamline pipeline conversion, retain customers, grow lifetime account value and turn loyal customers into advocates.

Rule #3: Always Outsmart The Algorithm

Predictive analytics are a means to an end — mechanisms to help grow the business and achieve marketing goals. For that reason, marketers need to first assess what success looks like for marketing initiatives in order to programmatically bring about the desired outcomes.

While it isn’t necessary to have full-fledged hypotheses for exploratory campaigns, marketers should have a clear understanding of the questions they’re trying to answer and why they’re relevant to the businesses. They should start with overall company objectives and then get granular.

On this point, Ramos is pretty clear about what not to do: don’t follow business technology’s big data lead. Don’t expect data or data technologies to answer the business challenges that have yet to be defined. And don’t expect technology partners to make sense of pools of data that may have been indiscriminately collected, even under the best or most earnest of intentions.

Recommendation: For usable insights, lead the effort in defining desired data outputs, and then working with internal and external partners for help in designing solutions. It is the proverbial “you reap what you sow” put into action — that the insights from the efforts will only be as good as the structure that is initially put into place.

Final Thoughts

Remember that today’s predictive analytics market is still in the very early stage. Marketers who are struggling to identify the "right" vendor and tools are not alone. The key to success with predictive analytics is knowing what your marketing organization needs. Often, you won’t know unless you try software for yourself — before making the decision to deploy a solution at a larger scale. It’s important to remain laser focused on major goals and test before you buy.

As SVP of Marketing at Radius, Angela Zener brings 15-plus years of experience in marketing. She has led teams responsible for launching global product lines across cloud, social and mobile for companies such as SAP, LexisNexis, and Findly.

Hearsay Social's Predictive Social Solution

Hearsay social placeitHearsay Social is a social media marketing management platform designed to help users engage with targeted social audiences.


The solution positions B2B marketers to manage their social media outreach and web presence from a consolidated dashboard.

Users of the solution can:

  • Receive recommended content to share though their social channels that is relevant to high-value prospects;
  • Schedule content and marketing campaigns to be posted throughout the week; and
  • Monitor posts and activity across Facebook, LinkedIn, Twitter and Google+ in real time.


Hearsay Social is compatible with Facebook, Twitter, LinkedIn Sales Navigator and Google +.


Click here to request a quote.

Competitive Positioning

Hearsay makes it easier for marketers to communicate and engage with prospects. The platform provides tools and analytics to drive relevant conversations to boost buyers' brand experiences.

Contact Information

Hearsay Social
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Lattice Engines Partners With Stein IAS, Expands Predictive Offerings To UK

Lattice scoring imageLattice Engines announced its partnership with Stein IAS, a global B2B marketing agency. The partnership is designed to offer predictive analytics services to Stein IAS clients and position Lattice Engines to expand its global offerings to the UK.

The partnership intends to provide Stein IAS clients with predictive insights that can enhance targeting capabilities and boost brand messaging to prospective buyers.

"With our broad spectrum of buying signals, marketing and sales teams can gather more accurate insights and achieve greater success in converting potential customers," said Michael Meinhardt, VP of Business Development and Strategic Alliances at Lattice.

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