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SalesStash Berkeley 2016

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SalesStash Berkeley 2016

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SalesStash Berkeley 2016

  1. Josh Tobin CS PhD student Frank Ong CS PhD student Martin Maas CS PhD student Patrick Castles EWMBA student Business development, partnerships, sales & marketing Engineering & product Engineering & machine learning infrastructure Business development, product, & machine learning infrastructure Helping sales teams find and deploy their best content https://www.youtube.com/ watch?v=DGLSfxmSkwM
  2. PART I How we got here
  3. BearSketch Make professional-quality graphics in seconds using the most natural user interface: hand-drawn sketches We all have to start from somewhere… Customer archetype Mid 20s – mid 30s management consultant working as a Business Analyst or Associate at a large firm. Value proposition Eliminate the work required for slide creation, allowing consultants to focus on higher value activities. Reduce the need for outsourcing. Key Technologies: Machine Learning, Computer
  4. SalesStash BearSketch Helping sales teams find and deploy their best content in seconds using machine learning Make professional-quality graphics in seconds using the most natural user interface: hand-drawn sketches …But how did we make it here? Customer archetype Mid 20s – mid 30s account executive / sales rep at a mid-large size technology company w/ a non-SaaS product Mid 20s – mid 30s management consultant working as a Business Analyst or Associate at a large firm. Value proposition Improve the effectiveness of your sales force by making it easy to leverage the best content you are already creating Eliminate the work required for slide creation, allowing consultants to focus on higher value activities. Reduce the need for outsourcing. • 100 interviews • 10+ mentor interactions • 5 MVPs Key Technology: Machine Learning
  5. Some themes of the things we learned Timesaving alone may not be a great value proposition Go where the money is A great product is not always a great business Focus on the biggest pain point
  6. An overview of our journey Close to the money Far from the money Minor pain point Biggest pain point 1 Sketches to slides 2 Automated slide cleanup 3 Automated slide design 4 Automated slide design 5 Deep content management Targeting sales teams Targeting consultants
  7. An overview of our journey Close to the money Far from the money Minor pain point Biggest pain point 1 Sketches to slides 2 Automated slide cleanup 3 Automated slide design 4 Automated slide design 5 Deep content management Targeting sales teams Targeting consultants
  8. What we thought… • Consultants sketch slides first • Converting sketches to slides is slow & painful • Consulting companies use outsourcing providers for this • Consulting companies would pay to save consultants’ time 1
  9. 1Initial business model canvas Reduce time spent on low- level activities Higher quality than manual design Lower cost than outsourcing Analysts at big consulting firms Analysts at financial services companies? Self support Individual vs. enterprise sales? Monthly license fees vs. per task/job? Premium features? What R&D? Customer Development Training Data R&D, Data, Cloud resources Starting from what we thought Some completely open questions But keeping an open mind…
  10. 1Sketches to slides – MVP
  11. … What we learned • Many different processes – not all sketch Consultants sketch slides first • Converting sketches is usually quick (except a few complex examples) Converting sketches to slides is slow & painful • Not all consulting companies outsource Consulting companies use outsourcing providers • Consultants thought we were solving the wrong problem! Consulting companies would pay to save consultants’ time 1
  12. Conclusion A great product does not make a great business! 1
  13. An overview of our journey Close to the money Far from the money Minor pain point Biggest pain point 1 Sketches to slides 2 Automated slide cleanup 3 Automated slide design 4 Automated slide design 5 Deep content management Targeting sales teams Targeting consultants
  14. What we thought… • Slide cleanup is a universal part of the slide creation process • Cleanup is necessary, but low value-add, painful and time consuming • Consultants will love this product and snatch it out of our hands 2
  15. 2Automatic slide cleanup – MVP
  16. … What we learned • People thought this was nice to have, but wouldn’t change the way they work Consultants will love this product and snatch it out of our hands 2 “If I had this and it worked well, obviously I would use it, but it feels more like an add-on to me” -Addie Bidder, Former Project Team Leader at BCG
  17. 2 Conclusion Add value beyond time savings!
  18. An overview of our journey Close to the money Far from the money Minor pain point Biggest pain point 1 Sketches to slides 2 Automated slide cleanup 3 Automated slide design 4 Automated slide design 5 Deep content management Targeting sales teams Targeting consultants
  19. What we thought… • If we allow customers to create designs that are infeasible to create themselves, they will value our product more highly • Consulting companies will invest heavily to make their teams more efficient 3
  20. Automated slide design – MVP 3
  21. … What we learned • Most firms would not pay enough to make this a large market Consulting companies will invest heavily to make their teams more efficient 3 “This is great, I would love to use it! But I’m not sure how much our firm would care – formatting doesn't really matter” -Dan Baldini Former Consultant at Deloitte
  22. We may also have some competition 3 BearSketch Google Docs Explore Released Sep 29, 2016 Auto-design slides, charts, pull in content from the web Powerpoint Designer Released Sep 26, 2016 Auto-design slides NEW!
  23. 3 Conclusion Move closer to the money!
  24. An overview of our journey Close to the money Far from the money Minor pain point Biggest pain point 1 Sketches to slides 2 Automated slide cleanup 3 Automated slide design 4 Automated slide design 5 Deep content management Targeting sales teams Targeting consultants
  25. What we thought… • Salespeople will have more or less the same pain points • They will have a higher bar for good design • Since more money is riding on each deck, sales teams will be more willing to pay for tools to help 4
  26. … What we learned • Salespeople have bigger problems! Salespeople will have more or less the same pain points 4 “If you built this, I would use it, but it wouldn’t change how I do my job. If you solve my other problem it would” -Mac Conn, Enterprise Account Exec at DoubleDutch
  27. 4 Conclusion Focus on the biggest pain point!
  28. An overview of our journey Close to the money Far from the money Minor pain point Biggest pain point 1 Sketches to slides 2 Automated slide cleanup 3 Automated slide design 4 Automated slide design 5 Deep content management Targeting sales teams Targeting consultants
  29. What we thought… • The biggest pain point for many inside sales teams in tech is access to and management of internal collateral • By matching sales decks with 3rd party content, we can add value to both • We can get around the issues with existing solutions using machine learning 5
  30. Deep content management – MVP 5
  31. … What we learned 5 “If this can really do what you say it does, I could take it to my Chief Revenue Officer right now.” -Ross Biestman, VP of U.S. Sales at Lithium
  32. PART II What’s next?
  33. The vision for SalesStash is to disrupt the market research industry Phase 1 2017 - 2018 Phase 2 2018 - 2019 Phase 3 2020+ Sales enablement through deep content management Insights marketplace – matching sales teams with the best 3rd party content AI-generated market research, leveraging our unique dataset (i.e., knowledge of what research people need) $600M TAM ~$4B TAM $40B+ TAM
  34. 2017 2018 2019 2020 Operat- ing plan $0M $1M $10M Product Proof of concept Sales Features Deep content management Insights marketplace AI-gen. research Initial customer 20-30 additional customers Build out sales org. Market research partners 100+ customers Content search Tool integration Content scoring 3rd party integration AI-gen. research We will raise money to fund each phase Angel 600k Seed 1.1M Series A 3.5M Series B 10M
  35. Outbound Sales Advertising Sales Blogs, Word of mouth Customer Trials Adding features Vendor lock-in through ecosystem Upsell to premium features (auto-design, additional data sources, slide ratings) We plan to use a freemium model Get Keep Grow
  36. Early hypotheses suggest CLTV/CAC ~15 Lead conversion Variable costs Cost / lead % Leads paid Lead stage Pipeline stage Trial stage CAC Premium product 8.5 60% 10% 33% 40% 386.36 Enterprise product 25 100% 10% 33% 40% 1,893.94 3rd party content 100 100% 25% 50% 20% 4,000.00 CLTV Price/unit Average deal size Churn Discount Commission CLTV 600 3 2% 10% 10% 6,075 2,400 12 2% 10% 10% 97,200 100 0.25 / customer / month ** ** ** **
  37. BearSketch People.ai Sales presentation tools is a crowded space, but this need is not well-addressed
  38. Final business model canvas Speed up content cre- ation by re- using existing material Record and predict effectiveness of material Sales & Marketing Professionals Get: Outbound Sales Monthly license fee Premium features: auto- design, content IP (ML/CV) Customer Development Training Data R&D, Data, Cloud resources Direct Sales to Enterprise R&D (ML, Integration) Marketing intelligence firms (Phase II) Sales Bloggers CRM Providers (coin operated) Insurance, legal, HR/Admin, recruiting, etc. Some parts of the canvas changed completely Other decisions were remarkably similar and our interviews helped us pick the right option
  39. Our product landing page goes live today www.salesstash.com

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