The importance of analytics for incentive programs 

Many channel-facing companies face a common set of problems when designing incentive programs. They don’t know what types of incentives to run for different channel partners. And they don’t know what channel partners are doing well, or not doing well, so they don’t know what they should be incentivizing.

Actionable insights are critical for obtaining the insights necessary to inform program design. Enterprising companies are increasingly using data analytics to expand the frontier of value creation in their pipeline.

McKinsey shows that 53 percent of “high performing” global sales organizations rate themselves as effective users of analytics. This is because this information guides stakeholders to more informed decisions that impact significant top-line and margin growth.

Although analytics have been widely heralded, they remain somewhat of a sideshow for a lot of companies. The same survey by McKinsey shows that most sales organizations today (57 percent) do not view themselves as effective users of advanced analytics. Many companies struggle to make informed business decisions using basic analytics, while some have yet to begin engaging with their data at all.

McKinsey found that utilizing data should be broken down into five stages:

Many B2B companies operate through a multi-tier distribution channel, involving distributors, resellers, dealers, agents, and more, making it difficult to monitor the behaviors and successes of their selling partners throughout the channel.

Savvy incentive program professionals combine sales and customer data to understand the intrinsic factors driving success, and use those factors as a feedback mechanism into designing future incentive programs. Channel-oriented B2B companies can then use real-time data to:

  • Measure the effectiveness of their incentive strategy
  • Communicate successes to their seller base
  • Provide training around areas which require improvement

They can also reward their channel partners for positive behaviors like high sales and brand advocacy, creating a positive cycle of increased loyalty and commitment to the brand.

Analytics-tooled companies harness data to understand what drives sales success, who is selling well, which products are popular, and which incentive programs function most effectively.