The role of Data Science
Data Science plays a critical role in consumer internet businesses. It is central to the economics of traffic, demand, conversion and user engagement. Companies rely on data-centric solutions to manage growth, improve traffic and conversion, fine-tune the user experience, and to optimize various parts of their operations.
And yet, leveraging data science in these key areas is something startups struggle to do. As they acquire traction and scale, they accumulate users and data fast, but don’t really know what they can do with it. In some cases the Data Science is slapped on to basic analytics and reporting; in others, Data Science gets pigeonholed in fairly narrow areas like predictive modeling for forecasting, risk analysis, or NLP applications.
In doing so, these companies miss a crucial opportunity. They are at a juncture where a single insight can unlock a new channel of growth or open up a new strategic trajectory for the business. Instead, they dip their toes tentatively, hire junior data hands or simply wait too long: in the process leaving money on the table, or missing a crucial turn in the road.
We think there is a better way.
The Short Proof difference
At Short Proof, we offer a way to lease a world-class team that hits the ground running. We bring end-to-end Data Science capabilities to companies in the consumer internet sector. We go beyond analytics and predictive modeling, and tackle the most crucial data-centric challenges of the business.
What we do
Often companies associate Data Science with simpler, descriptive questions like
- What is my user growth by region?
- How will revenue trend in the Northeast region?
… instead of questions like
- What kind of products and services should I build?
- What are the most important segments of my user-base?
- What features attract, engage each segment?
- What drives lifetime value for my customers, and how do I optimize for it?
- How do I retain my most valuable users?
At Short Proof, we answer business strategy questions using data and data science techniques, with precision and rigor. We then translate those answers into end-to-end execution, working closely with Product, Engineering, Marketing and Business Development teams. While we primarily focus on consumer internet companies, the principles and techniques apply equally to any business with a complex interplay among customers, partners and itself, reflected in large-scale data generated in its ecosystem. Some examples of such business strategy questions are:
- How to scale and grow the business by revenue/users/transactions or any other key measure of business value
- How to improve profitability of a business
- What product features should be built first
- What marketing strategy to adopt
- Which customers to acquire and how
- How to retain existing customers and grow their engagement
- How to assess and increase the lifetime value of a customer
- How to streamline and optimize business operations
How we do it
Answers to most of these strategy questions are often hidden in the patterns in data that customers leave behind as they interact with the product/service. If only the companies knew how to uncover and decipher those patterns…
We do exactly that — find patterns in large volumes of data that give deeper insight into why users behave the way they do, and how to 1) align the product/business strategy with that behavior OR 2) nudge the users into a behavior that creates lasting value for the users as well as the business.
Some examples of such behavioral insights could be
- What makes a user buy or subscribe to a product or service?
- What makes them stick with the product?
- What makes them engage more deeply with the product?
- What behavior leads to increase in lifetime value?
- What are the points of friction or failure modes along the way?
These insights then drive systematic product improvements using a methodology that spans data architectures, instrumentation, and rigorous A/B testing tools and practices. Throughout the process, we emphasize
- Injecting data and rigor into every aspect of strategic decision-making
- A nuanced quantitative understanding of complex user lifecycles
- Using (2) to drive product decisions and prioritization, and power the optimization of user acquisition machinery.
- Sophisticated growth management models that link user acquisition and spend optimization, lifetime value models, attrition prediction, re-engagement and incentive programs.
- Business model optimization, including keeping a tab on the pulse of a young user base and evolving user behaviors, and tweaking the relationship with the user to take advantage of discovered patterns and sidestep threats and risks.
As a team, we bring together extensive domain knowledge and experience; cross-functional capabilities that span analysis, research, engineering, product management and leadership; and expertise in a range of areas such as targeting and relevance, user interface optimization, A/B testing and data frameworks for the consumer web, marketing optimization, advertising and ad networks, monetization models, and optimization of supply chains and operations.
