The 4 Engagement Factors for Effective Incentive Programs

22 Jun 2020 · 42 min
41:39

In this 30‑minute webinar, Tim Harmon (Fielo) explains why most B2C and B2B incentive/loyalty programs under‑perform and presents a framework of four engagement factors that can dramatically improve channel‑partner programs and their ROI. He begins by citing industry surveys that show 77 % of consumer loyalty programs fail and argues B2B programs are similarly ineffective. He then outlines the three primary goals of incentive programs—boosting partner productivity, generating profit, and increasing engagement—and introduces a simple profitability formula (engagement × productivity – reward costs). The core of the talk is the four engagement levers: 1. Analytics – continuously measure what worked, recycle successful elements, and discard failures; use data‑warehousing and machine‑learning to surface insights. 2. Creativity/Innovation – apply gamified, time‑based models (race, front‑loaded/countdown), team‑based rewards, qualifier/play‑off structures, and developmental sequencing to keep programs fresh. 3. Change (Hawthorne Effect) – deliberately vary program design every 3‑6 months; short‑term programs sustain attention and avoid diminishing returns. 4. Partner Experience – deliver incentive information through integrated digital partner portals (Salesforce Community Cloud) that combine dashboards, chatter, and PRM functions, replacing outdated email‑spreadsheet communication. He illustrates each factor with real‑world examples (e.g., race model, qualification series, tier‑level programs) and shows a conservative financial model where a 45 % lift in engagement can raise net revenue uplift from $71 k to $1.1 M. The session ends with two audience Q&A items: (a) Fielo’s emerging machine‑learning analytics capability, and (b) when a forever‑running program can be justified (tier/level programs and bundling promotions). The webinar positions engagement as the primary driver of incentive‑program success and invites viewers to explore Fielo’s platform for implementation.

Questions this video answers

We are very active in R&D and engineering right now in building our machine learning capability, and we're working with a handful of our customers really on an alpha type of basis. So we're using our customers' input so that when we do come out with our machine learning capabilities in 2020, that it will have been with that customer stamp of approval that this is exactly what it is that they need and what will work for them.

There are two examples where a long‑running program makes sense. One is a tier or level program where partners earn points toward leveling up (e.g., silver to gold) over time. The other is a bundling promotion that rewards a seller each time they sell a combined product or service; this can be run on a long‑term basis.

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