Make search technology useful. Make the learning repeatable.
At Quattr, I connected enterprise customer questions with hands-on analysis, implementation support and reusable analytical methods.
Historical role: Senior Customer Success Manager and founding CSM.
Problem
Customers needed to turn search recommendations into work their teams could deliver.
My role
Customer discovery, analytical skill design, internal system building and technical delivery.
Decision
Connect customer context, a reusable method and an actionable output.
Output
The Growth Intelligence System, analytical reports and implementation follow-up.
Supported result
Customer recommendations, reusable analytical methods and a published delivery example.
Archived output · 19 November 2025
A defined place to start
812pages in the export→100shortlisted pages
First three ranked rows · page identities anonymized
Page
Clicks
Impressions
Queries
Priority score
Page 01
822
338,594
5,805
90.75
Page 02
88
101,932
2,424
25.09
Page 03
108
93,764
1,774
22.94
The decision to review: Page 01 surfaced with a priority-term signal. Review its demand and commercial relevance, then assign the next investigation. The score does not estimate incremental revenue.
Newly typeset, sanitized excerpt of the retained report; values preserved. Counts describe the export. The measurement window is not independently verified. Inspect the displayed values ↗
My contribution
Work between the commercial question and the technical answer
I investigated customer needs, reconciled data definitions and helped teams understand what a recommendation meant in their CMS, measurement setup and implementation process. I also designed analytical skills and built an internal Growth Intelligence System to make recurring questions more repeatable.
Quattr’s platform: the commercial product, agents and platform capabilities belonged to Quattr’s product and engineering work. My internal system: account context, analytical skills, runbooks and workflows that supported my analysis and customer delivery. Customer implementation: changes in customer environments involved their teams and relevant delivery partners.
From a customer question to a reusable method
A recommendation had to fit the customer’s page families, business definitions and capacity to act. I brought Snowflake-backed analysis, customer conversations and implementation context together, then shaped the output into priorities and follow-up.
The Growth Intelligence System gave that work a reusable structure: account context, a defined method and a deliverable with a clear next step.
Where do organic and paid search signals point to different priorities?
Does apparent content performance survive a closer look at coverage and lifecycle?
Which drivers and assumptions make a planning forecast useful?
Moneyball and TimesFM provide supporting examples of that reasoning in the flagship case, through cohort analysis and forecast planning.
Bring measurement discipline to AI search
I extended the work toward AI visibility, buyer questions and competitive research. A useful framework records the sample, source, period and decision it supports. Visibility and citations are different from referrals, leads and revenue.
The Growth Intelligence System connects runbooks, account ontologies, dataset resolution and an internal MCP interface. The case appendix shows sanitized configuration and skill excerpts with source context and archived examples.
Simpplr wanted to develop organic acquisition and reduce dependence on paid channels. I worked with its team as Quattr’s SEO concierge, including collaboration on conversion rate optimization. Quattr’s published case describes that work.
My contribution
Hands-on SEO concierge support and CRO collaboration with the customer team: turning platform insights into useful decisions and implementation conversations.
Platform and team delivery
The case describes Quattr’s unified paid and organic data, taxonomy, content workflows and automated internal linking, used by Simpplr’s marketing team.
Customer outcome
Quattr’s published case reports Simpplr’s organic growth and describes my SEO concierge and conversion-optimization work with its team.
Portfolio analysis example · Proposed requirements
Turning practitioner problems into repeatable product requirements
This fictional investigation illustrates how I turn a practitioner problem into proposed product requirements.
Start with the business question
A fictional enterprise software company markets its product on its corporate domain. Customer-operated subdomains serve different audiences: people using those customers’ services. A whole-domain view can mix buyer acquisition with customer activity. That separation keeps the analysis focused on the business question.
For “Where should corporate marketing invest?”, I would compare the corporate marketing scope, exclusions and selected market against a whole-domain view. I would inspect representative URLs, page purposes and audience intent, then reconcile the definition with the customer before drawing a conclusion.
Customer / GTM
Explain the decision
Show which audiences each scope includes, why customer activity can change the aggregate and which marketing question the narrower view can answer. Keep exclusions visible in the account explanation.
Product marketing
Explain the business value
Explain the incremental outside view alongside the customer’s existing analytics and marketing stack. Use the same audience-scoping scenario, with its inputs, interpretation and limits, to demonstrate where it helps answer the business question.
Product
Make the scenario reproducible
Provide a fictional corporate domain, customer subdomains, explicit exclusions and a selected market. Specify what should remain consistent when a practitioner changes views or exports the analysis.
Review the proposed acceptance criteria
Given a saved corporate marketing scope with customer-subdomain exclusions and a US market filter, preserve that definition across analysis views and exports.
Show the domain scope, exclusions, market, observation window and source assumptions beside the analysis and in the export.
When a practitioner changes scope, update the result and visibly identify the new definition; never silently broaden it.
Distinguish unavailable evidence from zero, and keep estimated visibility separate from first-party outcomes.
Preserve the agreed cohort and denominators when changing presentation; make a changed population explicit rather than comparing unlike totals.
If prompt evidence is introduced, retain the prompt text, provider, date, market and sampling method. Absence of prompt evidence must remain visible.
Proposed, not shipped. These are acceptance criteria for this illustrative investigation. Validation would require agreement on data coverage, product behaviour and the customer’s actual business question.
Explore the individual client engagements
Bluehost
Client engagement through Quattr
Role
Senior Customer Success Manager
Industry
Hosting and Web Infrastructure
Evidence
Engagement summary
Client relationship through Quattr.
Quattr tenure: December 2020–August 2026.
Customer SuccessEnterprise Enablement
CloudEagle
Client engagement through Quattr
Role
Senior Customer Success Manager
Industry
B2B SaaS
Evidence
Engagement summary
AI-assisted content prioritization and internal-linking work through Quattr. The published case reports the customer partnership’s outcomes.
Quattr tenure: December 2020–August 2026.
AI Search / GEOInternal LinkingAnalytics and Measurement
Coursera
Client engagement through Quattr
Role
Senior Customer Success Manager
Industry
Education
Evidence
Engagement summary
Consumer-learning search discovery, competitive demand and paid–organic query and landing-page analysis through Quattr. My scope here is analysis and recommendations.