Clear answers from the data you already have.

Crooked Wing Consulting does data analysis for businesses that have data but not the time or in-house analyst to use it. Fixed fees, plain-language findings, and no jargon.

Book an intro call See services and prices

Membership warehouse club: Showed that members who saw an in-app message were 2.3x more likely to use a new checkout feature.
Entertainment provider: Measured a holiday campaign that produced over 15,000 loyalty upgrades, with false conversions removed.
Fast-casual restaurant brand: Sized a $250,000 monthly revenue opportunity from a gap in how the app asks for push permission.

Services and prices

For when you don't have an in-house data wizard.

Every service is a fixed fee with a clear scope, so you know the cost and what you receive before we start. Select a service to see what is included.

Data Health Check $1,500 Find out whether you can trust your numbers, and what to fix first. 3-4 weeks What is included

Best for: businesses that report numbers but are not sure they are right.

What we do: profile your site, order, CRM and email data for gaps, duplicates and errors.

You receive: a prioritized fix list and a short plan for what to measure.

Not included: making the fixes.

KPI Dashboard Build $4,000 One dashboard that shows how the business is doing, kept up to date from your own tools. 4-6 weeks What is included

Best for: owners and managers who piece reports together by hand.

What we do: define 5-8 KPIs tied to your goals, then clean and connect your data sources.

You receive: a live dashboard, a metrics definitions sheet and a 60-minute team training.

Not included: data entry, historical record cleanup or daily reporting.

Customer Insights Sprint $3,500 A clear answer to one important business question, with the dollar opportunity attached. 3-4 weeks What is included

Best for: businesses facing a specific question, such as who their best customers are or where customers drop off.

Choose one question: a marketing segmentation audit (who your segments are, how each behaves, which to target), onboarding drop-off, re-engagement, upgrade conversion, feature adoption, an A/B test readout, or a CRM and lifecycle roadmap.

You receive: a findings report that tells the story in plain language, backed by SQL analysis and a comparison of groups, with the opportunity sized in dollars.

Not included: building or running the campaigns.

Marketing & Operations Audit $3,000 An outside view of how your marketing and operations really run, and what to improve first. 6-8 weeks What is included

Best for: owner-led teams where the work has outgrown the current processes.

What we do: interview your owner and staff, then review marketing channels and workflows.

You receive: an audit report and a prioritized automation and workflow roadmap, with suggested tools.

Not included: implementation, content creation, recruiting or lead generation strategy.

Add-on: Tracking Plan & Data Taxonomy $2,000 Keep your data consistent as your tools and team grow. After a Health Check or Dashboard Build What is included

What we do: define the events, naming rules and tagging logic used across your tools.

You receive: a tracking plan and a data dictionary your team can follow.

Not included: implementing the tags.

Results

Numbers from client projects. The case studies below show how the work gets done.

improvement in influenced revenue per download on research reports

400+

research results built and maintained as a portfolio for a sales team

$200k+

monthly revenue opportunity identified within days for an enterprise account

~900%

better reporting accuracy from fixing SQL errors in high-volume customer reports

Case studies

When it comes to data, brands are often left wondering “so what?” about their metrics. Our goal is to take the mystery out of the data: we help you measure what happened, explain why, and say what to do next. Client names are kept private, and projections are labeled as projections.

Membership warehouse clubCampaign measurement

Did an in-app walkthrough get members to use mobile self-checkout?

The campaign. The club showed a four-step in-app walkthrough of its scan-and-go payment feature to about 200,000 devices.

The analysis. I compared members who saw the walkthrough with members who had app sessions but did not see it, limited to those who had not used the feature in the prior 30 days. A conversion counted if checkout was completed within 72 hours.

What I found. 8.5% of members who saw the walkthrough used the feature, compared with 3.7% of those who did not. That is 2.3x more likely.

Entertainment providerCampaign measurement and attribution

What did the holiday campaigns do for loyalty upgrades?

The campaigns. In the fourth quarter, high-intent activity dipped across loyalty tiers, and nearly 3 million entry-level members were upgrading at only about 1% to 1.2%. The provider ran segmented holiday push and in-app campaigns.

The analysis. I set up the attribution logic: a strict 72-hour window for campaign views and a 30-day window for the organic baseline. I also removed false conversions, using suppression tags (such as geofencing and blackout states) to exclude users who received refunds or did not attend the event.

What I found. Campaigns aimed at existing members were about twice as efficient as general ones, peaking at an 8.02% conversion rate for the top-tier upgrade. A broad push to entry-level members drove over 15,000 upgrades in December, and late-December sends outperformed early-November starts.

Fast-casual restaurant brandFunnel analysis and recommendation

Why couldn't the brand message most of its new app users?

The situation. The app asked for push permission only after a first purchase, and about 72% of new users did not buy in their first session.

What I found. Winning permission took the brand about 71 hours on average, against a food and drink average of 25. Users who allowed notifications converted at 71%, compared with 32% for those who did not: 2.2x more likely to order.

Recommendation. Ask earlier with a clear value exchange, on exit or at the start of a second session, and leave the fast path alone for high-intent customers. This is a projection, not a measured result: converting 2% of the roughly 848,000 monthly unreachable users at a $15 average order would add about $250,000 a month.

Digital financial platformFunnel analysis and recommendation

Why didn't some users ever see their personalized advice?

The situation. After an in-app survey, tailored advice appeared in an in-app inbox, and push reminders were the main way users found it.

What I found. 45.9% of users with push turned on read their advice, and none of the users with push turned off did.

Recommendation. Add an in-app banner right after the survey that links straight to the inbox, so discovery no longer depends on push permission.

Global public service broadcasterFunnel analysis and recommendation

Why did so many app users never enter the welcome series?

The situation. The welcome messages started two hours after a user first opened the app, and only for users who had signed in by then.

What I found. Nearly 500,000 users signed in after the two-hour mark and were left out. Users also took about 50 hours on average to allow push, roughly 20% longer than the category average.

Recommendation. Start onboarding when a user signs in instead of on a timer, and ask for push permission earlier.

Published work

Articles, studies and customer stories on mobile engagement, onboarding and personalization, including the Mobile Lifecycle Measurement Framework.

Show 8 more articles

How to get started

Most clients begin with the Data Health Check. Its $1,500 fee is credited toward a Dashboard Build or Insights Sprint if you continue.

Book an intro call

Share your goals and the tools you use. It is free.
Receive a scope

A one-page scope with a fixed fee.
Approve and begin

Once you approve the scope, work starts.

What people say

“Jennie made complex concepts easy to understand and demonstrated real-world application with clarity.”
Client

“She has the right balance of technical knowledge and business acumen.”
Engineering executive, former colleague

“I have seen her shine in a variety of roles where she consistently delivers excellence.”
VP, Client Success, former colleague

About

Jennie Lewis is a value-focused researcher who transforms complex data into revenue-driving narratives. An expert in quantifying CX ROI, she began as a self-taught coder automating emails for GM before leading agency teams that supported iconic brands like Marriott, Chase, and Marvel.

She bridges the gap between technical data and business strategy, managing a portfolio of research results that achieve increased influenced revenue. Certified by Northwestern, eCornell, and Google, Jennie is a recognized thought leader and mentor dedicated to proving that great customer experience is a measurable driver of growth.

Jennie is a member of Women in CX, a global community for women in customer experience.

Credentials and recognition from