These 14 Startup Ideas Made The Cut For WashU Olin’s BIG IdeaBounce $50K Top Prize by: John A. Byrne on April 04, 2023 | 8,133 Views April 4, 2023 Copy Link Share on Facebook Share on Twitter Email Share on LinkedIn Share on WhatsApp Share on Reddit Team Name: EmployAI University: University of Pennsylvania, Wharton School BIG IndeaBounce 2023 finalist Concept: EmployAI is a decision intelligence platform for ecommerce executives that provides actionable strategic insights in boardroom-ready slides and an interactive dashboard. Challenge: Ecommerce companies today are collecting a lot of data that they want to use to drive strategy. Additionally, they are often stretched thin and it is hard for them to prioritize what they should be doing. Understanding the trends and drivers in their data helps them identify where to prioritize efforts and how to improve their business. However, most smaller ecommerce businesses do not have the internal data science resources required to conduct in-depth analyses. Without this, they often ended up dedicating time and resources to the wrong things. For example, many companies that we spoke to mentioned that if they see a drop in a key metric, it can take them several hours to days to figure out what happened. And even then they are not confident they’ve identified the right levers to explain the situation. These companies need more advanced data analytics tools to understand what drives changes in their KPIs, and ultimately impact decision-making in order to stay competitive in the current market. Solution: Our product is a decision intelligence platform that empowers non-technical users to better understand their data by providing insights through boardroom-ready slides, an exploratory dashboard, and email notifications. Our product works in four easy steps. First companies will connect our platform to their existing technology stack where they store data around their business. Second, they choose their north-star KPIs and mission-critical business questions such as repeat purchase behavior, basket optimization, customer segmentation, etc. Our platform then runs ML-augmented analysis to identify significant trends in the data. From there we provide the insights in 3 key formats. We offer boardroom-ready slides to make it easy for executives to understand the importance of the insights. We have an exploratory dashboard to make it easier for someone to understand why their metrics are changing by diving into the specific subcategories that have the biggest impact on the metrics. We also will have email notifications to alert users of anomalies or opportunities so that they are never missing out on ways to increase revenue. The Market: Our estimated opportunity is 142.5B. We arrived at this number by the following: take the 9.5 million websites in the US and multiply it by our annual average price per customer of $15,000. We believe our starting market is 4.5B which is the 300,000 Shopify customers with between 10-50 employees multiplied by our annual average price. We have determined that our ideal target customer to start is an ecommerce company with between 10 and 50 employees. At this stage, ecommerce companies have enough data available to conduct deep analytics but often do not have a full-time dedicated analyst or data scientist on staff. This is where we can have the biggest impact on an organization by providing machine learning-based insights to help the team prioritize and make decisions. The ecommerce industry is continuing to grow at a rapid rate meaning our customer market is constantly increasing. The estimated growth rate for the ecommerce market in 2023 is over 10%. Competition: There are four main options that e-commerce companies have available to them today, with varying pros/cons corresponding to each. There are two types of tools that provide simple analyses, and two main options for companies to leverage deeper Machine Learning-based insights. Companies can use ML-based tools to test hypotheses and combinations of data comprehensively. However, these tools are not geared toward non-technical users and require someone who is well-versed in data science to use the platform. Unfortunately, this is often not an option for startups that do not have data science teams. Additionally, companies can hire a data scientist but that requires a significant monetary and time investment. And ultimately, a data scientist can only run one analysis at a time and is often subject to biases about the data. On the other side of the spectrum, when looking for basic analyses, companies can leverage native reporting from platforms like Shopify or Hubspot. Additionally, they can use descriptive dashboards from visualization tools like Tableau or Looker. However, these tools can only highlight what has changed across your metrics and KPIs; they don’t tell you why it is changing. And that’s where our decision intelligence platform comes in. EmployAI makes data science accessible and actionable to all businesses and helps you answer the question: “why”. We leverage ML-augmented analytics to automatically test hypotheses in your data and pair that with easy-to-understand outputs built for executives. Another key differentiator is our delivery method. We provide outputs in three different formats: a) a boardroom-ready slide deck of the main findings b) push notifications for new anomaly detection across communications systems used within the company (e.g., slack, email) and c) an interactive dashboard that allows for further insight discovery Our automated platform and 3 tailored delivery methods help executives uncover revenue opportunities and set strategic priorities. Value Creation: After validating this pain point by talking to 30 companies, we secured two design partners who shared their proprietary customer data to serve as our first pilot. We received a lot of positive feedback from the companies about the value of the insights we have generated and the format of the insights using slides. One of our design partners is transitioning to a paying customer with a $1,500 monthly subscription starting in April. The Team: Amelia Cohen, MBA from Wharton, expected graduation 2023 Tara Balakrishnan, MBA from Wharton, expected graduation 2023 Previous Page Continue ReadingPage 5 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15