Predictive Analytics Applications for B2B Sales and Marketing Posted on : Apr 10 - 2017

The promise of predictive analytics applications for B2B sales and marketing is to generate revenue by expanding existing markets and penetrating new markets.

These predictive analytics applications are Software as a Service (SaaS)-based applications used in the sales funnel for both prospects and existing customers.

Traditional CRM lead management, Sales Force Automation (SFA) and Sales Intelligence (SI) offer some functionality to help Bb2B marketers and salespeople make better decisions. Today however, artificial intelligence (AI), data science and machine learning are now raising the bar.

Market Highlights

• Gartner estimates that the market for SaaS-based predictive analytics applications is approximately $100M – $150M.

• Solution offerings span many use cases — from segmentation to account selection, demand generation and upsell and cross-sell.

• Subscription contracts are typically two years or less and vendor churn at the end of contracts remains high due to unrealized expectations and the ease of switching.

• While there is differentiation in solution offerings, most vendors use similar messaging and positioning which creates confusion for buyers.

Popular Use Cases for Predictive Analytics

Total Addressable Market (TAM) Identification — B2B companies want to know how big of an opportunity exists before entering a market or making staffing and investment decisions.

Segmentation — Predictive models can be used to create segments of accounts based on signals (fit or intent) rather than simply on traditional firmographics.

Account Selection — Sales and marketing teams can identify the best accounts to select for outbound calling or for specific, integrated demand generation programs.

Integrated Demand Generation — Marketers, SDRs and ISRs can instantly expand the companies and contacts that they prospect versus buying lists.

Lead Scoring — Traditional lead scoring is typically based on two dimensions (demographic/ activity or firmographic and engagement). Predictive lead scoring incorporates buyer, company and market signals that are correlated with propensity to buy, in additional to traditional scoring.

Forecasting — Predictive forecasting models attempts to automate the forecasting and pipeline management processes by using data science models to score opportunities and roll them up at various levels.

Opportunity Scoring — Opportunity scoring helps sales management understand the true likelihood of close (and the close date) instead of going off what the rep has entered by leveraging historical data.

Upsell / Cross-sell – Upsell and Cross-sell models provide not only the accounts to target, but also the solutions to offer by analyzing internal data.

Outcomes Expected

B2B sales and marketing organizations are turning to predictive analytics to increase their bottom line and competitive advantage. Some of the most outcomes expected include:

• Improve win rates, deal velocity and increased deal size
• Increase revenue in existing markets
• Increase share of wallet with existing accounts
• Generate revenue in new markets
• Increase conversion rates throughout the sales and marketing funnel
• Increase marketing’s contribution to the sales pipeline
• Increase ROI on marketing spend
• Optimize the allocation of sales and marketing resources
• Cut down lead volume and increase revenue and productivity
• Increase SDR call utilization rates
• Decrease expenses by eliminating unproductive leads

In summary, predictive analytics applications can provide an “unfair” advantage to B2B sales and marketing teams. Specifically, adopting SaaS-based predictive analytics applications can help a B2B marketing team by improving segmentation, account selection, demand generation and lead scoring to increase conversion rates and contributions to pipeline and revenue. In addition, adoption of SaaS-based predictive analytics applications can help a B2B sales team improve forecasting, pipeline management and upselling/cross-selling to increase win rates, deal velocity and average sales price. Source