Our predictive-financial projection technology uses company data sources for growth.
Trend #1: Demand for decision-ready data - Provides a greater contribution to decision readiness of performance data - Per 2019 Gartner research, switch to “sufficient sources” of truth from a single source generated 40% greater contribution to decision readiness, and improved decision making and business outcomes by more than two times. Trend #2: (Re)centralization of finance analytics - Finance must determine which types of analysis should be owned by the center or the line and develop a scalable partnership model to sustain high-quality customer service. - Provide better decision support once the organizational model is properly aligned to specific activities.
Competitive landscape: Set A: Bench, Intuit, NetSuite, Sage, Xero, SAP, FreshBooks; Set B: Finpro, Finmark, Pry. 1. Demand for decision-ready data: a. Accounting: Set A b. Projections: Set B 2. (Re)centralization of finance analytics: a. Finance professional access: Set A b. Layperson as end-user: Set B c. Single source of truth: Set A 3. Reporting on demand: a. Charts and reports: Set A and set B b. AI and ML: Set A and set B c. Readily accessible: Set B Accounting and single source of truth are mature markets. Finance professional access, charts and reports, AI and ML, and readily accessible are competitive markets. Layperson as end-user is an opportunity. Finpro's true edge: Layperson focus, ready to use inputs, visualization-focused
1) Solidifying target audiences, creative direction, the “why” across the customer funnel -awareness, conversion, loyalty 2) Building the diverse content stream necessary to be successful via digital channels 3) Rigorously testing initial marketing strategy via calculated soft launch roll-out 4) Evolving strategy based on soft launch learning, expanding strategy via hard launch 5) Growing market share by continuously addressing all aspects of the customer funnel - awareness, conversion, loyalty 6) Reaching top converting audiences consistently and directly at scale