As a decision maker: Create one consistent data view across tools and eliminate costly redundancies
Based on a decade of experience, we understand your needs:
- Accurate event data, ideally with guaranteed quality
- Consistent data across different teams and tools
- Data that enables your teams to efficiently do their job
Our product is built on the belief that decision makers should be able to make data-driven decisions and not have to worry about the underlying data. We provide analytics / clickstream / event data like SaaS. With our Data as a Service (DaaS), everything is done for you:
- We collect your event data (implementation included)
- We monitor and validate your data, handle any issues
- We optimize your data for usability
We guarantee quality event data to support your uses.
A new and modern approach to collecting and using event data: Single Source of Truth by design
From a data architecture perspective, analytics tools, data stacks, and marketing technologies are all just data pipelines that consist of the same components:
- Creating / collecting data
- Processing data
- Storing data
- Using data / creating value
Instead of having all these solutions create redundant, usually inconsistent, and often low-quality data, it’s better to create data only once and focus on its quality.
With our DaaS, you can stream the same data into different MarTech tools, analytics solutions, and data pipelines to ensure overall consistency and remove redundancies.
Up to 40% lower cost than options without guaranteed data quality
By standardizing and automating our implementation process and building lots of automated services around it, we are able to offer you very competitive pricing.
You will also receive a refund for every day that quality standards are not met, and we will resolve any data issue at no additional cost. Who wouldn’t like that?
You need to measure everything to answer the why, not just the what
You can’t manage what you don’t measure. And if you don’t measure enough, a lot of questions remain unanswered making it difficult to provide actionable insights.
You may have been given this advice before: Focus on a few important data points and make sure that data is accurate and reliable. We strongly disagree with this limiting approach.
Transactional data answers the what, event data answers the why. So to answer the why, you need a complete picture of what happened, as anything can affect a user’s behavior.
Our Data as a Service aims to cover everything. And if something is missing and technically possible, we add it.
For a flat fee: Ready-to-use, high-quality event data
Analytics vendors offer tools, agencies offer consulting services. We provide the end product, the data, as a service.
With data quality and reliability being our sole focus, we enable you and your stakeholders to focus on your use cases.
Similar to SaaS, our Data as a Service approach is worry-free and about 40% more cost-effective than traditional models.
We integrate seamlessly with your existing software solutions and service providers by taking care of the implementation.
The difference between DaaS and agencies / consultants
More than a decade of consulting and helping clients with their data issues has made us realize that the approach to collect data to create value is inherently broken.
Most companies work with their service providers on their data collection together. Unfortunately, shared responsibilities don’t work for increasingly complex implementations.
Instead, we recommend to make the data and its quality the responsibility of just one party so that the deliverable can be measured, and somebody can be held accountable.
Our DaaS comes with a data quality guarantee and can be used by you and your partners. We believe that agencies create a lot of value, but data creation requires undivided attention.
Enabling all your use cases that require quality event data
- Machine learning and artificial intelligence
- Marketing spend allocation / ROI optimization
- User journey and user behavior analytics
- Product analytics / user experience analytics
- Dashboards and reports, e.g. for management
- One 360 degree view on the customer or user
- Ecommerce analytics, e.g. checkout funnels
- Conversion rate optimization (CRO)
- Churn reduction
- Customer activation
- Dynamic pricing
- a/b/n testing and personalization
Got a use case that isn’t listed here? Please let us know.
One tool-agnostic, future-proof, and cost-effective implementation for everything
Our implementation is the last one you’ll ever need, and you don’t have to lift a finger. We’ll replace all your current legacy implementations and data collectors with just one.
Free your websites and apps from legacy code slowing them down (maybe even breaking them) to make a lot of people very happy:
- Your users and customers
- Your UX / site reliability team
- Your security and compliance team
The data we collect for you can be used with all kinds of marketing technologies and data stacks.
What Cape.ly does
- Collect event data and provide it to downstream consumers
- Work with your IT on our highly automated implementation
- Guarantee the data quality based on 10+ years of experience
What Cape.ly doesn’t do
- Store data long-term or provide analytics features
- Read from downstream consumers or do reverse ETL
- Not an agency, a data lake, a CDP, or an analytics tool
Everything on the left is taken care of for you. The tools and use cases on the right show how you can use our DaaS to create value.
Your goals are automatically our goals due to our business model
You need high-quality data continuously, not just now, because data use cases take time to implement and usually get more profitable over time.
Our business model is built around long-term partnerships. Everything we do is thought through and meant to work for a long time.
We have learned from a decade of experience that quick fixes, workarounds, and makeshift (or band-aid) solutions don’t last.
We have huge initial implementation efforts, so if we don’t earn your business for a second year, we lose money. This sets us apart from other service providers.
Fixing data issues downstream is exponentially more expensive
A high-quality implementation to collect high-quality data costs more than a low-quality one, but dealing with low-quality data incurs even more costs downstream.
You have probably heard of “garbage in, garbage out” (or GIGO), which further contributes to the problem: The further downstream you move, the less likely it gets that you can actually fix your data.
That’s why our platform includes:
- Data models optimized for data science use cases
- Schema enforcement and data contracts
- Constant adjustments to evolving environments
- Event data based on best practices from a decade of experience
Keep your data compliant with privacy rules and regulations
Your data is one of your biggest assets, but could also be one of your biggest liabilities due to legal compliance requirements.
Reduce your risk with our legal compliance framework that covers North America and Europe. We also support a variety of Consent Management Platforms.
Coming originally from Europe, we have many years of experience dealing with strict privacy laws. That’s why, with just a few clicks, you can set up:
- Cohort-based analytics
- and more!
Obsession for quality and more than a decade of experience
Hey there, my name is Ian and I am the founder of Cape.ly.
For over a decade now, I have architected analytics implementations and debugged them at the network and source code level to deliver the best event data possible.
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.
When aiming to maximize conversion rates, increase average cart values or set individual prices for products and services, optimization and personalization efforts require data.
Identifying what drives conversions allows funds to be allocated efficiently. Consent-aware cohort-based or fully anonymous tracking can provide a full picture.
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.
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.
“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.
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.
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.
Due to more focus on privacy, browsers and mobile apps make it increasingly difficult to collect behavioral data, which requires sophisticated data collection strategies.