Prospecthouse Digital — Growth Marketing Lead Take-Home Task

Brief 01

Lead generation — Google Ads from scratch

Structure and distribute a $10,000/month Google Ads budget across two services

Context

PestShield is a pest control business operating across Sydney. They offer two services:

⚡

Emergency pest control

Same-day and next-day response for active infestations — spiders, cockroaches, rodents, and ants.

🔍

Termite inspections & treatment

Pre-purchase and annual termite inspections, active infestation treatment, and ongoing monitoring programs.

Twelve months ago PestShield ran Google Ads for one month, spending $10,000. It generated very few leads and was shut down. They’ve now engaged Prospecthouse to build and manage the account properly, with a monthly budget of $10,000.

Your task

Stage 1—Questions for the client

Before building anything, what are your highest-priority questions for PestShield?

Stage 2—Build your recommendation

Using the information in this brief, answer your own questions. State clearly where you’re making an assumption and why. Then address each of the following:

How would you structure the campaign and ad group architecture?

How would you distribute the $10,000/month budget across the two services, and why?

How would you monitor campaign success? What information do you need from the client to know whether the campaigns are actually working?

Brief 02

E-commerce — Meta performance & attribution

Review last month’s performance data and tell us what’s going on

Context

Flux is a DTC wellness brand that sells a single organic shampoo — one product, one SKU. They have 12,000 existing customers, a small retail store, and an established base of retention activity across SMS and email. The business has consistently done between $120,000 and $180,000 in monthly revenue. Meta ads were introduced two months ago. Below is last month’s performance data.

Last 30 days — performance data

Meta Ads Manager

Ad spend	$15,000
Reported revenue	$135,000
Reported ROAS	9.0×

Shopify

Total store revenue (all channels)

$160,000

Your task

What do these numbers actually tell you? What questions does it raise, and what are your must-know questions from the client?

The client thinks Meta ads, since being introduced two months ago, are amazing because of the high ROAS number. What are your thoughts on this?

Brief 03

E-commerce — Google Shopping account review

Audit and reallocate budget across a live Performance Max account

Context

RunDNA is a specialty running retailer operating in Australia. Their Google Ads account runs Performance Max campaigns segmented by brand — one campaign per brand, plus a Catchall campaign for all remaining inventory. Each campaign runs with a daily budget cap and a Target ROAS bid strategy.

You’ve inherited this account as a new account lead. You’ve been asked to review performance, identify what is and isn’t working, and recommend how to reallocate budget and approach the account going forward.

June 2026 — campaign performance

→ Click any campaign row to explore the product breakdown

	Campaign	Daily budget	Target ROAS	Clicks	Impressions	Search IS	Cost	Conv.	Conv. value	Conv. value/cost

Your task

Stage 1—Questions for the client

Before making any changes, what questions would you ask RunDNA? Consider what the data doesn’t tell you that would materially affect your recommendations.

Stage 2—Your analysis and recommendation

Looking at the campaign data and the product breakdown within each campaign, what stands out to you? Walk through what you see.

What is the single biggest structural problem in this account, and why does it matter?

What additional data or inputs from the client would sharpen your recommendation before you made any changes?

Brief 04

Creative — UGC creator brief

Identify a creator persona and write a brief ready to send

Context

Pega Sports is an Australian soccer brand worn by A-League professionals, NPL players, and recreational players across the country. It’s mid-season, peak winter — the period when compression base layer sales historically spike.

Pega has just expanded their Compression Long Sleeve Top into 2XL and 3XL, adding to an existing XS–XL range. The top is now available across all eleven colours and all sizes. Pega wants to use a UGC creator to help promote this product. Products can be given to the creator.

Product

Compression Long Sleeve Top — pegasports.com.au

Price	$37.50 AUD
Fabric	Polyester / Spandex blend
Full size range	XS, S, M, L, XL, 2XL, 3XL (2XL and 3XL new)
Colours (11)	White · Black · Red · Royal Blue · Navy Blue · Sky Blue · Dark Green · Emerald Green · Yellow · Orange · Pink
Audience	A-League professionals, NPL players, recreational players

Your task

Identify the UGC creator persona you would engage for this campaign. Describe who they are and why you chose them.

Write the creator brief. It should be no longer than one A4 page and ready to send.

Brief 05

E-commerce — blended performance deep dive

Analyse four months of raw account and store data and tell us what’s really going on

Context

Marlowe Coffee Co. is an Australian DTC specialty coffee roaster selling single-origin beans and blends, one-off and via subscription. The business does roughly $180–230K in monthly revenue across paid, organic, and a well-established email/SMS retention program.

The account was previously managed by a freelancer who handed over at the end of June. You are taking over as the account lead from 1 July.

One complication: Marlowe replatformed their site in late February, and in-platform conversion tracking has been unreliable since — treat reported conversions and reported ROAS as unavailable. Marlowe and Prospecthouse work off blended metrics instead.

How we measure

MER	Total store revenue ÷ total ad spend
aMER	New-customer revenue ÷ total ad spend
nCAC	Total ad spend ÷ new customers acquired

Commercial inputs

Contribution margin	~55% of revenue after COGS, shipping, fulfilment and transaction fees (before ad spend)
AOV	~$70 — new customers ~$74, returning ~$66
Repeat behaviour	Average customer places ~2.3 orders in their first 12 months; 12-month revenue per new customer ≈ 1.9× their first order

The data

Two CSVs, daily, covering 1 March – 30 June 2026. Download both below.

marlowe_ads_daily.csv

One row per campaign per day across Meta and Google: date channel campaign spend impressions clicks — no conversion columns (see above).

marlowe_shopify_daily.csv

One row per day: date orders revenue new_customer_orders new_customer_revenue returning_customer_orders returning_customer_revenue orders_with_discount discount_amount

Your task

Stage 1—Questions for the client

Before (or while) digging in: what would you want to ask Marlowe, and what additional data would you request? State any assumptions you end up making and why.

Stage 2—Your analysis and recommendation

What happened in this account and business over the four months? Walk us through it the way you would walk the client through it.

What specifically drove the changes you found? Be precise — which campaigns, which dates, what magnitude, and how you know.

You own this account from 1 July. What would you do with the budget in July and why? Where you can, quantify the expected impact in contribution-margin dollars — not just ratios — and note the risks and how you’d validate your changes.

Guide: we’d expect this brief to take roughly 2–3 hours. Use whatever tools you like — spreadsheets, Python, BI tools, AI — we care about the quality of your findings and your reasoning, and you should be prepared to walk through how you got there.