Hey there, my name is Ian and I am the founder of Cape.ly
For over a decade, I have been helping companies with their data challenges and coaching employees on how to enable their organizations for successful data initiatives:
- Individual contributors, technical and non-technical
- Team leads, directors, vice presidents, and C-level
A few good strategic decisions can be game-changing, especially at the management level.
If that sounds interesting to you, you can learn more about past projects on my profiles on Cape.ly and LinkedIn, or on my personal website.
Cape.ly does not provide any consulting services that are not related to our Data as a Service. But I may be able to help if time permits and your project piques my interest.
Obsession for quality and more than a decade of experience
My work with medium-sized to large companies in North America and Europe has provided me with a wealth of experience and a unique combination of traits:
- Stereotypical German obsession for quality
- Stereotypical Canadian kindness
- US business based in fast-paced NYC
I believe very few have as deep an understanding of all the client-side and server-side technological details that affect data quality and reliability as I and other team members do.
You can find more information about past projects on my profiles on Cape.ly and LinkedIn, or on my personal website.
Increase conversion rates through personalization
When aiming to maximize conversion rates, increase average cart values or set individual prices for products and services, optimization and personalization efforts require data.
Optimize marketing spend by measuring 1st-party interactions
Identifying what drives conversions allows funds to be allocated efficiently. Consent-aware cohort-based or fully anonymous tracking can provide a full picture.
Reduce churn by reacting to customer behavior in real-time
Most companies accept churn and are only trying to reduce future loss. However, there are usually clear indicators that customers may churn that can be used to prevent it.
Make confident decisions through a single source of truth
Instead of having many tools create redundant, usually inconsistent, and often low-quality data, it’s better to create data only once and focus on its quality.
Inaccurate source data causes snowballing costs downstream
“Garbage in, garbage out” is a huge problem, but the costs increase exponentially, because the further downstream the more effort it takes to fix data, if it’s even possible.
Switching to a new analytics solution won’t fix data issues
Instead of admitting that the implementation is not right, data teams often blame the tool. However, a new tool without an improved implementation won’t produce better results.
Don’t treat analytics as one-off implementation projects
Even though most never do, some new implementations may produce quality data at first. However, it requires constant effort to maintain that level of quality.
Don’t underestimate technical data collection challenges
Due to more focus on privacy, browsers and mobile apps make it increasingly difficult to collect behavioral data, which requires sophisticated data collection strategies.
