How to Use Kompyte for Marketing — 5 Practical Use Cases

Use Kompyte to systematically track competitor activities, product changes, pricing updates, and marketing strategies. Turn competitive data into actionable intelligence for your team.

1. Identify your top 5-10 competitors and the intelligence categories you need to track
2. Set up monitoring in Kompyte for competitor websites, social media, job postings, and press releases
3. Create a competitive intelligence dashboard with weekly updates on key changes
4. Analyze competitor content strategies, messaging, and positioning shifts
5. Share intelligence summaries with product, sales, and marketing teams monthly

Leverage Kompyte to design, distribute, and analyze customer surveys. Understand preferences, satisfaction levels, and unmet needs to inform your marketing strategy.

1. Define your research objectives and the specific questions you need answered
2. Design the survey in Kompyte with a mix of quantitative and qualitative questions
3. Keep surveys under 10 questions and under 5 minutes to complete for maximum response rates
4. Distribute through email, in-app, and social channels to reach diverse respondents
5. Analyze results with cross-tabulation to find differences between segments

Use Kompyte to identify and track market trends that impact your industry. Stay ahead of shifts in customer behavior, technology adoption, and competitive dynamics.

1. Define the trend categories relevant to your business (technology, behavior, regulatory, economic)
2. Set up trend monitoring in Kompyte with relevant keywords and data sources
3. Track leading indicators that predict market shifts before they become mainstream
4. Create quarterly trend reports with implications for your marketing strategy
5. Present trend findings to leadership with recommended strategic adjustments

Use Kompyte to create data-driven audience personas based on actual customer research. Move beyond fictional personas to evidence-based profiles that drive better marketing decisions.

1. Gather data from customer interviews, surveys, analytics, and CRM records
2. Analyze the data in Kompyte to identify distinct behavioral and demographic clusters
3. Create 3-5 personas with demographics, goals, pain points, and preferred channels
4. Validate personas with sales and customer success teams who interact with these segments daily
5. Update personas annually with fresh data to prevent them from becoming stale fiction

Leverage Kompyte to research optimal pricing through competitive analysis, willingness-to-pay studies, and conjoint analysis. Data-driven pricing decisions protect margins and accelerate growth.

1. Map competitor pricing across all tiers, plans, and packaging options
2. Design a pricing research study in Kompyte: Van Westendorp, Gabor-Granger, or conjoint analysis
3. Survey target customers and analyze willingness-to-pay by segment
4. Model revenue impact of different price points and packaging scenarios
5. Present pricing recommendations with supporting data and sensitivity analysis