Griffith Consulting Group
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service · data engineering

Data engineering for small businesses, in plain English

Your business creates data with each sale, booking and message. We collect it, clean it and turn it into answers you can check. You don't need a data background to work with us.

Book a call How it works
fig. 1 · messy records in, a clear chart out

What you get

  • One table of your leads

    Each lead and order in one place, with a note on where it came from.

  • Counts you can trust

    Duplicates merged and labels fixed, so the totals come out right.

  • Answers to your questions

    You bring a business question. We answer it with your numbers and show the math.

  • Charts you can share

    Charts you can read at a glance and share with your team.

How it works

Five stages, shown with sample records from a fictional bakery. Open any stage on the home page to step through the rows yourself.

  1. Data mining: find what you already have

    A sample bakery keeps its leads in three places: a booking sheet, a message inbox and a website form. Mining means gathering the data you already own into one table.

    you get each lead in one place, with a note on where it came from

    More about data mining

    3 of 17 sample rows, from three sources
    namefromorder
    Ana Ruizsheet$64
    Gabe Mossinbox18
    Marcus Bellform120.00

  2. Web scraping: add what's public

    Scraping is one way to mine. A small script collects public information, like competitor prices and review counts, so you can compare yourself to the shops down the street.

    our rule public pages only, within each site's terms

    More about web scraping

    Sample public data for four bakeries
    shopcakeratingreviews
    Corner Crumb$364.6212
    Sugar & Rye$424.898
    Oven Door$304.1341
    You$344.757

  3. Data cleaning: fix the mess

    One customer can show up twice, and one channel can carry three spellings. Left alone, those slips give wrong counts. We standardize labels, merge duplicates and turn prices into numbers.

    you get counts you can trust

    More about data cleaning

    • walk inWalk-inone label
    • Marcus Bell with a trailing spaceMarcus Bellduplicate merged
    • $64 · 95 · 48.0064 · 95 · 48prices as numbers

  4. Data analysis: ask a question

    Analysis starts with a business question. For the bakery: which channel brings customers who place orders, and how much do they spend?

    formula order rate = orders ÷ leads

    More about data analysis

    referral leads, after cleaning

    order rate 3 orders ÷ 4 leads = 75%

    average order ($64 + $95 + $48) ÷ 3 = $69

  5. Data visualization: see the answer

    A chart turns the table into something you can read at a glance. Then you decide what to do about it.

    you get a clear picture and a next step to test

    More about data visualization

Why you can trust the numbers

  • You see the rows. Each chart traces back to the records behind it.
  • We say what we don't know. If your data can't answer a question, we tell you and suggest what to start tracking.
  • Plain English. Reports explain what changed and what to try next.

Data helps you make the next call with more confidence than a hunch. You still make the call.

Who it's for

Small businesses where one of these sounds familiar:

  • Your sales, bookings and messages sit in separate apps, with no single view.
  • You make big calls, like which offer to push or when to hire, on a hunch.
  • You want to compare your shop with the competition using public information.

Questions owners ask

Have another one? Ask it on a call.

Do I need to understand data to work with you?

No. You need to know your business. We handle the data and explain each finding in plain English.

What public data do you collect?

Public information like competitor prices and review counts. Our rule: public pages only, within each site's terms.

What if my data can't answer my question?

We tell you, and suggest what to start tracking.

Can I check the numbers myself?

Yes. Each chart traces back to the records behind it, and our reports explain what changed and what to try next.

Other services

We build the systems first, then put the data they collect to work.

Tell us what's piling up

Describe the mess in a few sentences. We'll reply with where we'd start.

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