Experimentation / CRO

Experimentation and Testing Programs acknowledge that the future is uncertain. These programs focus on getting better data to product and marketing teams to make better decisions.

Research & Strategy

We believe that research is an integral part of experimentation. Our research projects aim to identify optimization opportunities by uncovering what really matters to your website users and customers.

Data and Analytics

90% of the analytics setups we’ve seen are critically flawed. Our data analytics audit services give you the confidence to make better decisions with data you can trust.

PXL Blueprint

Why PXL?

Most experimentation programs start with prioritizing ideas based on a model like ICE or PIE. If you want to improve your prioritization you move on to PXL Model. It is much more detailed and tailored to A/B-tests ideas and hypotheses.

ICE and PIE models are subjective, based on who’s calling the shots about the changes. But the PXL model is more nuanced, with added questions like—Is the change above the fold? Changes above the fold are noticed by more people, thus increasing the likelihood of the test having an impact. Is the change noticeable in under 5 seconds? If not, it’s likely to have less impact.

How you prioritize your experiments matters. A lot. Prioritization models help you base your experiments and changes on valid foundations like user research, other data, the change’s impact, and a lot more. They are also great when you have a big backlog of ideas, to sort and prioritize them right. Prioritization models will help you get out, start things right, and dig gold from the dirt.

Use Cases:

- Prioritize your experiments based on objective standards.

- Help someone who’s only starting experimentation.

Type:
Artifact
Pillar:
Planning & Process
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Toolkit includes PDF of the blueprint, and if available links to related assets and a loom video on using the blueprint.