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:
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.
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.
“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 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.
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.
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.
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.
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.
Radius announced $50 million in Series D funding that the company intends to use to scale its predictive marketing software platform and meet the growing demand for its solutions.
This investment will be applied toward further development of the Radius Predictive Marketing Software platform as well as the company’s proprietary data science engine and data cloud.
The funds come during a time of notable growth for the company, with its revenue increasing by more than 400% in the past year. The company has also doubled the number of employees during that period.
The latest round of investment was led by Founders Fund, which brings Radius' total funding to $125 million.
“The expectation is that ‘the data is out there,’ but no matter how many tools, scientists, or databases they acquire, CMOs struggle to gain the insights necessary to effectively pursue the largest market opportunities,” said Darian Shirazi, CEO and founder of Radius.
The integrated solution uses purchasing signals and predictive data to segment prospects by buying stage and display relevant ads.
As buyers interact with campaigns or websites, those behaviors are shared with the predictive intelligence platform. This feature intends to make messaging cohesive and update in real time based on buyers’ needs.
"By integrating predictively scored companies, and key contacts within those companies into campaigns as a single solution, we help our customers reach the right prospects with relevant content, at scale, with no extra work on their part," said Amanda Kahlow, CEO and Founder of 6sense.
6sense and Bombora Partner On Predictive Tool For Real-Time Ad Targeting
The integrated solution uses purchasing signals and predictive data to segment prospects by buying stage and display relevant ads.
As buyers interact with campaigns or websites, those behaviors are shared with the predictive intelligence platform. This feature intends to make messaging cohesive and updates in real time based on buyers’ needs.
Lattice 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.
While it is not a new strategy, account-based marketing has recently become a critical part of the marketing mix. More than 90% of marketers believe that account-based marketing is a “must-have,” according to SiriusDecisions’ 2015 State of Account-Based Marketing (ABM) Study. While just 20% of respondents are currently using an ABM approach, 60% expect to adopt a targeted account approach over the next year, according to the survey.
"Account-based marketing has been a viable and successful strategy for B2B for the past decade, but the tools that are available now make it much more attractive to implement," said Megan Heuer, VP and Group Director at SiriusDecisions, in an interview with Demand Gen Report. "There is a greater opportunity to take advantage of ABM because today's technology makes it much less labor intensive."
To succeed at ABM, many savvy B2B marketers are relying on predictive analytics to focus on the accounts on their targeted list that are showing the highest propensity to buy. “The majority of ABM programs have a list of targeted accounts in the 500 to 2,000 range, so that is still a lot of activity that is hard to track manually,” said Heuer. “Predictive is the one thing that enables companies to scale their ABM efforts, something which was not possible even a few years ago.”
Demandbase, which offers an ABM platform, is using predictive tools to boost its own ABM strategy. “To accelerate our account-based marketing efforts, we required a scientific understanding of the highest value companies to target,” said Peter Isaacson, CMO of Demandbase. “By organizing our sales and marketing efforts around these high value accounts, we have better aligned our teams and significantly increased our pipeline.”
Using predictive tools from Lattice Engines, Demandbase identified the key characteristics of its closed accounts and late-stage pipeline. Armed with that data, the sales and marketing team then developed a list of target accounts. The result was a 75% increase in close rates and 72% increase in average selling price compared to accounts identified through traditional lead scoring tactics.
Demandbase measured the success of its ABM strategy using three metrics:
“Where predictive can help in ABM is looking beyond the firmographic and demographic data to really identify the buying intent data of that account,” Nipul Chokshi, Head of Product Marketing for Lattice Engines. “Predictive can zero in on intent data such as participation in forums on third-party networks or when members of a buying committee at a targeted company download syndicated white papers, attend webinars, view videos and click on ads.”
Using buyer intent data is a critical component of predicting which accounts are more likely to purchase, according to observers. “If you have an account in which for the past few weeks, multiple contacts have been researching a new phone system and downloading white papers about new phone systems, that not only tells you if they meet your buyer criteria, but it tells you they’re in the market now,” said Alison Murdock, VP of Marketing for 6sense.
CSC, a provider of IT products and services, is piloting a predictive platform in partnership with 6sense to identify new buying intent within its strategic accounts as well as new business opportunities. CSC uses models and digital buying signals to understand if a specific targeted account is showing increased interest in a particular solution area. The marketing and sales teams then work together on a coordinated approach.
“ABM isn’t a choice; it’s a necessity,” said Nick Panayi, Director of Global Brand and Digital Marketing at CSC. “We have to go to market in a focused, highly targeted way. Our products and solutions are quite sophisticated, and we support mission critical environments in large customers and governments.”
Panayi noted that the company also offers content recommendations to all website visitors based on their digital body language, but those recommendations are even more accurate for targeted accounts. “How well you can predict a buyer’s behavior is a direct function of what you know about them. When it comes to ABM accounts, we clearly know more about their content consumption habits and are able to make more accurate predictions about the content that will engage them.”
Overlaying predictive analytics with other attributes of successful accounts can help marketers further target their messaging. “This has helped many of our clients have more fact-based and relevant conversations with their targeted accounts,” said Lattice’s Chokshi.
Chokshi noted that one client, a tech consulting firm, has used predictive tools to identify target accounts that have had a recent change in IT leadership. The firm then developed specific content for those specific accounts.
In another client example, Chokshi said a storage device manufacturer determined that companies that have recently invested in content management systems are more likely to buy than companies with other characteristics. They targeted those accounts with use cases around the role of storage needs and content management.
The future of ABM will likely involve tighter integration with CRM, marketing automation and additional tools for more precise ad targeting.
“We’re very excited about additional integration with marketing automation and some of the new things we’re seeing and new things from LinkedIn to help with targeted ads,” said Jessica Cross, VP of Marketing for Fliptop. “Anything to make those connection points work more seamlessly will make it easier to succeed at account-based marketing.”
Radius, a predictive marketing software company, has expanded its marketing and sales executive team.
The four new members of the executive team are David Obrand, COO; Jerry Clarno, VP of Sales; Andrew Garvin, Senior VP of Strategy; and Angela Zener, Senior VP of Marketing.
Obrand was previously Chief Customer Officer at Yammer. He also served as CEO of Fuze, a creator of cloud-based communication technology. Obrand also spent a decade at Salesforce in senior sales roles.
Clarno brings more than 20 years of experience building and scaling sales teams, including stints at Box, SuccessFactors, OneLogin and FedEx.
Garvin come to Radius after working with Peter Thiel and Ajay Royan on the launch of Mithril, a growth stage venture fund with $540 million in assets under management.
Zener brings more than 15 years of experience in marketing and management consulting and has successfully taken many new enterprise software offerings to market.
“We are thrilled to have David, Jerry, Andrew and Angela as part of the Radius family during this exciting period of hyper growth for the company,” said Darian Shirazi, Founder and CEO of Radius. “These talented executives have been instrumental in building some of the most successful SaaS companies over the past decade and we look forward to leveraging their collective experiences as we scale the organization to deliver best in class products and customer experience.”