If you are a rapidly-growing tech startup, you probably have three potential growing pains that we can help you with:
- Performance Issues. You have already outgrown your technology stack and DevOps infrastructure. Product features, in-house tools, or services that used to work lightning fast are slowing to a crawl or timing out. Your internal team have noticed and are complaining, and perhaps even your customers have started to complain. It’s symptoms like this and more that suggest you have a database or infrastructure problem, but you’re not sure what to do next in order to fix it.
- Where are our metrics? And what do they mean? You need to make a data-driven decision, but you can’t get enough data, and what you get doesn’t make sense, and maybe even takes a long time to get. Perhaps you have multiple data. Maybe you installed Google Analytics early on but now you’re struggling to understand it or customize it. Maybe you are ready to do a marketing campaign but don’t know which users are your best (most engaged, most retained, most profitable).
- Skills Gap. Maybe you have an idea for a data-driven product, tool, or feature. Maybe it’s a recommendation feature, or a tool to rank popularity. Or perhaps you simply want to check off on your growing company’s todo list the box, “Get a data scientist” because you heard how cool and great they are (which is true, of course). Or you’ve realized that there are a number of things you need done by someone who can work with data: statistical analysis, mining and wrangling data, data warehouse architecting, growth hacking, visualizations, survival analysis, marketing segmentation, smart alerting, artificial intelligence agents.. the list goes on. You don’t just need someone, though, you need an entire team, and ideally one who has experience solving the same problems in your business.
Below are more detailed examples of solutions we have provided to our clients:
- Exploratory data analysis, data mining, ad-hoc questions and queries, with report outs in various formats.
- Building data-driven features into your product, including:
- Recommendation Systems, Collaborative or Content Filtering (“You May Also Like…”)
- Predictive Tools, Anomaly Detection (“We’ve detected unusual activity…”)
- Ranking Algorithms (“Top 10 Sports News Articles This Hour…”)
- Interactive data visualizations, dashboards, ongoing reports
- Data quality. Cleaning, munging, wrangling unstructured or semi-structured data into meaningful results
- Modernization of legacy systems. Replacing, upgrading, or wrapping the old to produce the new
- Analytics Platform Deployment, Customization, and Integration (e.g. Data warehouses or other parts of the stack or pipeline)
- Analytics Consulting – strategy and counsel regarding building your own data engineering or data team internally, platform selection and choosing the right technology, model development, decision process re-engineering
- Data Privacy, Protection and Policy Guidance. If you are collecting data about your customers, you need to understand the rights and responsibilities you have, as well as the rights and responsibilities of your customers. What is considered “compliant” varies by geography, industry, format, platform, and even age group — and continues to evolve. We stay informed of the trends so we can help our clients make intelligent decisions.