Advanced Analytics: The Next Technology Frontier For Sales And Marketing Organizations
- Written by Matthew S. McKenzie
- Published in Data Management
Sales and marketing analytics have long shared one common trait: An addiction to Excel spreadsheets. According to one study conducted by the Business Performance Management Forum, 73% of marketing executives use spreadsheets for analytics, while nearly 80% rely on spreadsheets for forecasting.
Now, some experts say, a growing number of analytics tools might give both sales and marketing organizations better – and far more automated -- decision-making and forecasting capabilities, while also ultimately serving the cause of sales and marketing integration.
Craig Moore, Service Director of Marketing Operations Strategies at SiriusDecisions, said this new crop of advanced analytics tools moves decision-makers away from manual analytics processes and towards more advanced predictive capabilities. "Business intelligence focuses on past performance," Moore stated. "Predictive analytics forecasts behavior and results in order to guide specific decisions."
A Fast-Growing Market For Predictive Analytics
For sales and marketing organizations, typical predictive analytics activities include sales forecasting, details on expected buying behavior and propensity to buy, as well as "defection detection" to predict and prevent customer churn. The analytics applications may draw data exclusively from a CRM or marketing automation platform, although they more commonly integrate data from multiple enterprise applications, including (for the largest companies) "big data" repositories that aggregate vast quantities of enterprise data.
According to Moore, about 15% of B2B marketing organizations currently use advanced analytics tools with predictive capabilities, and this number could double within the next 2-3 years. "The tools are evolving to the point where they're useful to business analysts, as opposed only to [business intelligence] experts," Moore said. "There's a great opportunity for them to use analytics techniques and tools to gain greater insights."
On the marketing side, Moore cited a number of vendors that provide advanced analytics solutions with predictive capabilities, including Opera Solutions, MuSigma and PivotLink. While some of these solutions tend to require a high level of customization and on-premises resources, others – such as GoodData and Birst – have SaaS-based offerings and third-party app ecosystems that require a relatively simple implementation process.
Many marketing automation and CRM platforms also include traditional analytics that provide a dashboard-based view of current performance and, in some cases, comparisons to historical trends. As a rule, however, these built-in analytics tend to be less robust than stand-alone analytics solutions. This has created an opportunity for advanced analytics vendors to integrate their offerings with popular CRM and marketing automation tools; GoodData, for example, offers analytics apps for Salesforce, Pardot, Microsoft Dynamics CRM and SugarCRM, among others.
Historical Data Drives Sales Forecasting
On the sales side, one of the better-known advanced analytics vendors is Cloud9 Analytics, which has developed a forecasting application that combines customer relationship management (CRM) with business intelligence (BI) functionality. The goal, according to Cloud9 CEO Jim Burleigh, is to replace a spreadsheet-based approach to forecasting with a more quantitative approach that uses historical data to predict future sales performance.
"CRM systems keep virtually no history at all – you get a pile of data," Burleigh said. "What you want out of that data is more insight or intelligence, more valuable answers. What people do to get that is to apply spreadsheets and fall back on gut instinct. That's still how most insights are gained in sales organizations today." In addition to its forecasting capabilities, Cloud9 is also designed to provide greater visibility into the sales pipeline; it can, for example, identify at-risk deals based upon historical trends extracted from salesforce.com or another CRM system.
Similar Problems, Different Needs
For B2B sales and marketing organizations, advanced analytics technology raises at least two important issues. First, there's still a significant gap between tools designed for either side of the sales-marketing relationship – and that gap will take time to close.
"Inherently there's not much distance between the two; the problems are similar," Moore said. "But the vendors working in the space today tend to take either a sales-oriented or marketing-oriented approach because that's simply where they started."
As the vendor solutions mature, Moore added, he expects to see a convergence process that brings together sales and marketing analytics into integrated solution portfolios. "There are lots of [shared] problems that need to be solved, such as the use of sales-enablement resources and linking those to closed deals," Moore said. "Is that a sales or a marketing problem? It's really both, since both teams need to understand which assets are helping to drive closed deals."
As vendors head towards convergence, however, they must also deal with the unique differences between sales and marketing analytics. Denis Pombriant, CEO at Beagle Research Group, said the highly dynamic nature of sales reporting demands an approach to collecting and analyzing data that isn't applicable to marketing analytics tasks. "In marketing you can apply analytics to a single state of the market, but if you try to do the same with sales you're toast," Pombriant said. "Sales data is different from marketing data, and so are the ways we analyze it."
Analytics, Alignment And Implementation Challenges
In spite of those differences, however, Burleigh said that both types of analytics ultimately serve the same goal: driving tighter alignment and integration between B2B sales and marketing organizations.
"You need to go several steps deeper into closed-loop reporting that analyzes the process of how leads turn into deals," he stated. "When a lead turns into an opportunity that doesn't turn into a closed deal, why did it happen? Was it a bad lead? Or was there something wrong in the sales process?" The answers to these questions have to come from the sales organization – and from their sales analytics tools – but they're vital to establishing a closed loop between sales and marketing.
For organizations looking to implement advanced analytics for either sales or marketing, Burleigh said he advises beginning the same way an organization would launch a CRM initiative: with strong leadership.
"You need an executive sponsor who will say 'we are going to take this leap," he said.
Second, Burleigh said, organizations should be prepared for advanced analytics tools to expose gaps and shortcomings in existing – but often poorly managed – data sources. "When they see the power of the analytics, and they look at more fine-grained details as a result, they see that the data in their CRM systems has problems," he said. "But you've got to get your team managers and executives using the data, and using the results of the analytics, before the people who enter the data – such as the field sales reps – will see the value of entering data more accurately and in a timelier manner."
"It's a change management issue," Burleigh concluded. "Any time you have a system that's going to point out problems and holes [in current sales and marketing processes] there's naturally going to be resistance."