Stitched Insights is a Silicon Valley SaaS start-up that has built a proprietary machine learning system that helps companies better understand their customers. Born out of world class research from the University of Pennsylvania and turned into a commercially useful product, the company now works with several Fortune 500 companies providing deep customer insight quickly and efficiently. Stitched Insights believes the future is in listening to customers, not asking them questions, and has built a suite of tools for organizations to do just that.
We just launched into commercialization mode, in commercialization mode, we’ve achieved paid pilots with: Thomson Reuters, 3M along with other well-known brands and mid-market clients. We're aiming to convert these to SaaS contracts within this year.
Sentiment analysis is a big market (TAM) that every company must have in order to understand their customer and grow their business. Surveys are currently the go-to for these insights.
For example: the average cost of a survey is approx 120K, each brand runs 2-4 of these a year - each org that we’re dealing with has at least 10 brands - more than half of the fortune 1000 companies use surveys - that's over $4B.
Problem or Opportunity
Sentiment analysis is a big market (TAM) that every company must have in order to understand their customer and grow their business. Surveys and panels are currently the go-to for these insights (over $4B). SI Platform creates the ability for brands to have 10x faster and more accurate insights. We have a competitive advantage in retail and a scalable model today. Over time, as we add AI depth and new industries, we’ll scale horizontally across industries - increasing our competitive strength and creating an incrementally larger market for emotion analysis.
Solution (product or service)
Unstructured customer feedback, open-ended survey answers, public reviews and internal interactions such as support requests can be passed to Stitched Insights and immediately used to identify new psychographic insights around touchpoints that drive perceptions and behavior like trust and churn. This can be used to measure the effectiveness of new and old campaigns, optimize workflows and prioritize product changes.
Breakthroughs in deep-learning natural-language processing (NLP) research gives teams AI ranked psychographic insights about any market or product based on existing feedback data - enabling brands to anticipate opportunities and risk to their customers’ happiness.
1) Integrate.ai: we like Integrate.ai’s strategy of improving their customer’s existing AI models (which validates a need for better data) but we’re different because we focus on generating new insights that leverage emotion. 2) Infibond: they are playing in a more related space but is using a different (less scalable) approach. Our data science team has previously tried the Infibond approach of supervised learning and has found that unsupervised and semi-supervised approach is key to being able to derive *novel* insights that may not have been thought of ahead of time (i.e. hypothesis generating) and to make this scalable in order to penetrate varied domains and markets.
Advantages or differentiators
We've developed new proprietary language analysis models to process customer text in any language using unsupervised methods/deep learning. Our ability to scale globally across many languages and capture competitive data for our clients has proven to be a significant differentiator in this space.
Right now we have 3 enterprise partners that we're doing pilots with. We're really focused on 1) getting more commercial use cases 2) getting larger data sets - thus we're pricing our pilots really low 10-20 thousand - our pilots are typically 30-60 days and expecting expanded pilots to lead to annual subscriptions. Based on current data, customer acquisition cost is between 10-30 thousand and lifetime value is approximately 1.1 million.
We’ve recently introduced a free 30 day trial subscription with 70% Q/Q increase in signups. We have 2 sales channels: 1) Direct-to-Brand (such as retailers and manufacturers) and 2) Reseller Partners (such as market research partners and systems integrators).
- Platform-as-a-Service with a free 30 day trial. - 2 main sales channels: 1) Direct-to-brand SaaS 2) Reseller Partners API integration - Average annual contract: $120,000-480,000 - CAC: ~$25,000 - LTV: $1.4M
Money will be spent on
Accelerating sales and operational excellence to prepare for series A.
F500 budgets are scarce due to covid concerns. We have made substantial sales progress none-the-less in the past couple of months!
Incubation/Acceleration programs accomplishment
- GSVlabs Portfolio Company
Won the competition and other awards
- IEEE Startup Competition Winner 2018 - Dr. Johannes Eichstaedt (CSO): Scientist of the Year (in recognition of the “Twitter predicts Heart Disease” paper in Psychological Science) (Philly Geek Awards); Elected as an “Emerging Leader in Science and Society” to rethink mental health care delivery in interdisciplinary team (American Association for the Advancement of Science (AAAS); Awarded King’s College’s highest honor, the Jelf Medal, presented to the most distinguished graduates (10 out of 4,500) (King’s College London)