Small firms, real problems, fast builds. We love this work, we create real value, and every client we’ve worked with will take your call.

The situation

Inbound leads arrived as raw, unstructured emails from the company's Atlas Branding WordPress contact form. Each one was re-keyed by hand into a CRM, with a person manually splitting the information into separate contact, organization, and deal records.

Where value was leaking

Every lead cost minutes of manual data entry and re-keying. Records were inconsistent, follow-up was slow, and the owner had no clean pipeline view — the value of each lead was leaking between the website and the CRM.

What we built

A PKDO-designed CRM plus an automated lead-intake pipeline. A raw inbound email is now parsed automatically and formatted into three structured records — Contact, Organization, and Deal/Opportunity — with no manual touch.

Value created

• Manual re-keying per lead reduced to effectively zero
• About 10 minutes of manual work per lead, eliminated.
• One raw email → three clean, structured records, automatically
• Consistent records eliminate the typos and gaps of hand entry

Stack

Next.js · TypeScript · automated email parsing · structured CRM data model

Proof & status

Live pipeline: each new website lead lands as three formatted records automatically. Replaces a standing manual data-entry task.

The situation

An established gallery with a base of collectors and buyers, but little visibility into which customers actually drove revenue, and no web analytics in place to connect online interest to sales.

Where value was leaking

Without segmentation, marketing and outreach were spread evenly instead of concentrated on the highest-value collectors. There was no way to see recency, frequency, or monetary value — or to spot high-value buyers going quiet.

What we built

An RFM / RF$ (recency, frequency, monetary value) customer-segmentation model that ranks the collector base by value, plus a full Google Analytics implementation to measure the web-to-gallery funnel.

Value created

• At-risk high-value buyers flagged for targeted re-engagement
• Marketing effort redirected toward the highest-RF$ segments
• Web traffic finally measurable and tied to outcomes
• For the first time the gallery could see which collectors were worth pursuing and which had likely moved on, so outreach effort went where it could actually pay off.

Stack

RFM / RF$ segmentation model · Google Analytics · reporting layer

Proof & status

Effectively the proof-of-concept behind PKDO's Haywood Analytics product — the same Pareto / at-risk-revenue logic, productized.

The situation

A WNC outfitter offering guided fly fishing and outdoor experiences, a destination business that depends on travelers and locals finding them in search before they book a trip.

Where value was leaking

Qualified visitors were not converting to bookings at the rate the business could support: organic search visibility for high-intent queries was uneven, paid acquisition was not tightly measured, and the web strategy was not aligned to the actual buyer journey from discovery to inquiry.

What we built

An ongoing analytics, SEO, SEM, and web strategy engagement. Structured analytics to see what was actually working, on-page and technical SEO targeted at high-intent fishing and outdoor experience queries, measurable paid search campaigns, and a web strategy tuned to turn searchers into qualified inquiries.

Value created

• Meaningful lift in organic visibility for high-intent guided trip queries
• Paid spend made measurable, cost per inquiry and cost per booking tracked not guessed
• Web flow tightened so qualified search traffic converts to inquiries at a higher rate
• Acquisition decisions now made on data instead of intuition

Stack

Google Analytics, Google Search Console, Google Ads, on-page and technical SEO, web strategy iteration

Proof & status

Active ongoing engagement. Both organic and paid channels delivering measurable improvement against pre-engagement baseline.

The situation

A local music and media organization whose audience data, email marketing, and contact management lived in disconnected places, with no analytics layer to measure what was working.

Where value was leaking

Content and outreach decisions were being made without data. Audience growth was hard to measure, email engagement was invisible, and there was no unified view of contacts.

What we built

A Google Analytics implementation, an email-marketing system, and a CRM — integrated so audience, engagement, and contact data finally lived together.

Value created

• Unified audience and contact data in one place
• Email engagement (opens, clicks, list growth) made measurable
• Content decisions backed by analytics instead of guesswork
• Repeatable marketing workflow instead of ad-hoc sends

Stack

Google Analytics · email-marketing platform · CRM integration

Proof & status

Integrated analytics + email + CRM stack, live.

The situation

A large festival running many events across many venues over multiple days, with scheduling coordinated through manual tools.

Where value was leaking

Coordinating a multi-day, multi-venue, multi-event schedule by hand is error-prone and time-consuming, and leaves attendees and staff without a reliable single source of truth.

What we built

A custom multi-day, multi-event, multi-venue scheduling application — one authoritative schedule for the whole festival.

Value created

• Single source of truth for the entire festival schedule
• Coordination time cut versus manual spreadsheet wrangling
• Fewer scheduling conflicts across venues and time slots
• Better attendee and staff experience

Stack

Custom scheduling web app · structured event/venue data model

Proof & status

Used to run a live multi-day, multi-venue festival schedule.

The situation

An independent cafe wanting customer loyalty without the cost of a custom app or the hassle and lost-card problem of paper punch cards.

Where value was leaking

Paper punch cards get lost, capture zero customer data, and give the shop no way to re-engage customers. A native app is overkill and too expensive for an indie cafe.

What we built

Brew Loyalty: a mobile-first digital stamp card. Customers scan a QR code, enter a phone number, and get a digital card; baristas add stamps from an admin view; customers earn a reward at the target. No app download.

Value created

• Customer contact data captured at the counter (vs. zero on paper)
• Re-engagement now possible — you can reach the customer again
• No app-download friction; works in the browser
• Productized at $19/mo per location with a 28-day free trial

Stack

Next.js 15 · TypeScript · Tailwind 4 · Supabase · QR generation/scanning · PWA

Proof & status

Live product. Owner Audrie Blomquist quoted on the PKDO home page — a real, named testimonial.