🌈  Neil Andrew

Founder at Lunio, one of the UK's most exciting AdTech SaaS scaleups, where I've taken the business from bootstrapped beginnings to 60+ employees, $20m+ raised in venture capital raised, contributed to 7-figure deals and generated 8-figure recurring revenue streams.

We eliminate invalid traffic (IVT) across your performance marketing media buys, ensuring you only pay for real, legitimate, human traffic and your data is actionable & clean.

If you're a founder at a startup or scaleup open to networking please reach out. I'm always looking to expand my network and learn from others where possible!

Angel Investor & Member

🌈 Neil Andrew

🥇37X Award Winning Independent PPC & CRO Consultant | £500M media spend managed & over £2B generated in sales across +170 brands

👋🏼 Hello! I'm Jack, the UK’s #1 Independent Google Ads consultant helping in-house teams and brands achieve 10/10 results across PPC.

In the last year I’ve won more than 30 Awards for my work across the UK and Europe as well as Globally, more on this here: www.jack.tm/awards/

Over the last 16 years I’ve worked with over 170 different brands from Rightmove, Addison Lee, Worldpay, Confused.com and On the Beach, to Castore, Secretsales.com, Hays Recruitment and Cole Buxton.

I specialise in 3 things:

💰Helping brands cut wastage, by reducing the amount they pay Google to acquire New Customers (and how much they pay to re-acquire Exisiting ones)

📈Re-investing these savings into incremental, profitable New Customer Acquisition (increasing Revenue, ROI, Margins and Profits)

🤖Deploying World Class Automation and AI that really works, so that we can get more done, quicker and more effectively

Here’s some of my recent results:
www.jack.tm/case-studies/

My experience covers a wide range of sectors, including retail, property, recruitment, finance, fintech, martech, automotive, travel, advertising and education, from start-ups to global multi billion £ companies.

Get in touch and request a free audit below:
https://calendly.com/jacktm

All the best,

Jack

Contact: jdfelstead@gmail.com
Web: www.jack.tm

Jack Felstead

Here are the results from a test I recently launched on Google Ads (Search Campaigns).

𝙏𝙝𝙚 𝙜𝙤𝙖𝙡 𝙬𝙖𝙨 𝙨𝙞𝙢𝙥𝙡𝙚:

→To test a Google "best practice" Consolidated Campaign Structure vs. a Segmented Campaign Structure.

𝙏𝙚𝙨𝙩 𝙘𝙧𝙞𝙩𝙚𝙧𝙞𝙖:

→Same date range and test duration, same keywords, same budgets
→2 Consolidated Campaigns vs. 18 Segmented Campaigns
→Test has been live for just under 4 weeks now
→Non-brand keywords only

𝙏𝙝𝙚 𝙧𝙚𝙨𝙪𝙡𝙩𝙨 𝙨𝙥𝙚𝙖𝙠 𝙛𝙤𝙧 𝙩𝙝𝙚𝙢𝙨𝙚𝙡𝙫𝙚𝙨:

✅ 59% lower Cost per Click
✅ 13% higher Conversion Rate %
✅ 64% lower Cost per Conversion
✅ 19% lower Cost
✅ 122% more Conversions
✅ 96% more Clicks

I have used the same segmented approach for the last 10 years, and it still gets the same results, for one simple reason:

𝙄𝙩 𝙢𝙖𝙠𝙚𝙨 𝙨𝙚𝙣𝙨𝙚. Here's why:

I segment Campaigns according to "Main Segments" which in this case are:

→Keyword Type (Brand & Non-Brand)
→User Location
→Device
→Keyword Match Type

All these main segments perform differently from one another in terms of CPC's, Conversion Rate % and so on. So it makes sense to segment them.

This approach allows me to do 2 things that are not possible using a consolidated/broad approach:

𝟭. 𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝗯𝘂𝗱𝗴𝗲𝘁𝘀 𝗮𝗰𝗿𝗼𝘀𝘀 𝘁𝗼𝗽-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗰𝗮𝗺𝗽𝗮𝗶𝗴𝗻𝘀 & 𝗱𝗲𝗰𝗿𝗲𝗮𝘀𝗲 𝗮𝗰𝗿𝗼𝘀𝘀 𝗽𝗼𝗼𝗿𝗲𝗿 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗲𝗿𝘀 ✅ 

𝟮. 𝗔𝗱𝗷𝘂𝘀𝘁 𝗕𝗶𝗱 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 (𝘁𝗖𝗣𝗔/𝘁𝗥𝗢𝗔𝗦) 𝗮𝗰𝗰𝗼𝗿𝗱𝗶𝗻𝗴 𝘁𝗼 𝗲𝗮𝗰𝗵 𝗰𝗮𝗺𝗽𝗮𝗶𝗴𝗻𝘀 𝘁𝗿𝘂𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 ✅

Instead of letting Google's Black Box Algorithm decide what's working and what's not, I decide, and I action, based on more transparent, actionable data.

But, this approach needs to be deployed correctly.

💬 Comment "𝗣𝗣𝗖" below and I will send you the step-by-step guide including:

1→How to choose your main segments
2→The negative keyword strategy I apply
3→The advanced bid strategy I apply
4→How I portion Campaign budgets
5→How I decide optimal Bid Strategies to maximise performance

All results are 100% true and legitimate, please feel free to question/challenge me on these, I am happy to provide further context/data (without revealing any confidential client data of course).

Here's how I've been using advanced AI to optimise Google Ads accounts lately...

It's as simple as asking the AI the following:

"𝐭𝐞𝐥𝐥 𝐦𝐞 𝐭𝐡𝐞 𝐚𝐛𝐬𝐨𝐥𝐮𝐭𝐞 𝐭𝐨𝐩 𝟏𝟎𝟎 𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐈 𝐜𝐚𝐧 𝐜𝐚𝐫𝐫𝐲 𝐨𝐮𝐭 𝐰𝐢𝐭𝐡𝐢𝐧 𝐭𝐡𝐢𝐬 𝐠𝐨𝐨𝐠𝐥𝐞 𝐚𝐝𝐬 𝐚𝐜𝐜𝐨𝐮𝐧𝐭 𝐭𝐨 𝐢𝐦𝐦𝐞𝐝𝐢𝐚𝐭𝐞𝐥𝐲 𝐢𝐧𝐜𝐫𝐞𝐚𝐬𝐞 𝐛𝐨𝐭𝐡 𝐑𝐎𝐈 𝐚𝐧𝐝 𝐑𝐞𝐯𝐞𝐧𝐮𝐞 𝐮𝐬𝐢𝐧𝐠 𝐚𝐥𝐥 𝐭𝐡𝐞 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐟𝐞𝐚𝐭𝐮𝐫𝐞𝐬, 𝐬𝐞𝐭𝐭𝐢𝐧𝐠𝐬 𝐚𝐧𝐝 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 𝐈 𝐡𝐚𝐯𝐞 𝐜𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐞𝐝 𝐲𝐨𝐮 𝐰𝐢𝐭𝐡"

Here's how it works:

1. The AI plugs directly into any Google Ads account's 1st party data

2. It uses Big Data to get ALL the available data within the account, so it has a 100% clear picture of what's working, what's not, and what needs to be done to improve performance

3. The AI is configured with over a dozen advanced, deeptech features, and over 200+ custom rules, settings and layers (directly from our 37X Award Winning Strategy)

4. It then analyses the account in depth to identify the absolute top 100 actions that we can carry out right away to increase both ROI and Revenue for this brand

5. Within minutes, it presents all 100 actions in an easy to read, actionable, phased roadmap, with expected uplift in ROI and Revenue over the next 7 to 28 days

This isn't just plugging a LLM directly into your Google Ads account.

This is much, much more than that.

This is the important (🔒secret) stuff:

"𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐟𝐞𝐚𝐭𝐮𝐫𝐞𝐬, 𝐬𝐞𝐭𝐭𝐢𝐧𝐠𝐬 𝐚𝐧𝐝 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 𝐈 𝐡𝐚𝐯𝐞 𝐜𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐞𝐝 𝐲𝐨𝐮 𝐰𝐢𝐭𝐡"

👉 Like this post and Comment "𝗔𝗜" below and I will send the (anonymised) output of the prompt featured within the video.

Let me know if anyone has any questions on what AI's capabilities below, keen to discuss how other people are using AI to optimise their Google Ads accounts.

⬇️ This 𝗙𝗥𝗘𝗘 sheet allows you to 𝗔𝗖𝗖𝗨𝗥𝗔𝗧𝗘𝗟𝗬 𝗧𝗥𝗔𝗖𝗞 𝗔𝗜 𝗕𝗥𝗔𝗡𝗗 𝗩𝗜𝗦𝗜𝗕𝗜𝗟𝗜𝗧𝗬 and mention it directly inside Google Sheets.

𝗙𝗼𝗿 𝗔𝗘𝗢 (𝗔𝗻𝘀𝘄𝗲𝗿 𝗘𝗻𝗴𝗶𝗻𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘀𝗮𝘁𝗶𝗼𝗻) & 𝗚𝗘𝗢 (𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗘𝗻𝗴𝗶𝗻𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘀𝗮𝘁𝗶𝗼𝗻) 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴:
→ Add your prompt list, brand name, and domain
→ Automatically check what ChatGPT, Claude, Gemini, and Google AI say
→ Log brand mentions, domain links, and all brands cited
→ Store the full response for week-over-week comparison

𝗙𝗼𝗿 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴:
→ See when competitors get mentioned and you don’t
→ Spot drops after model updates
→ Track visibility trends over time inside Google Sheets
→ Remove manual testing completely

☑️ No new tools
☑️ No API setup
☑️ No manual checks
☑️ No manually testing prompts in ChatGPT
☑️ No guessing if AI tools ever mention their brand
☑️ No checking one model at a time, randomly
☑️ No relying on screenshots instead of real tracking

If AI is influencing buyers, this is how you measure it.

✅ Comment “𝐓𝐫𝐚𝐜𝐤𝐞𝐫”
✅ Like this post
✅ Follow me

And I’ll send it to you for 𝗙𝗥𝗘𝗘.

Credit for this post goes to the legend Adriaan Dekker

Here's how I 𝐮𝐬𝐞 𝐀𝐈 𝐭𝐨 𝐡𝐞𝐥𝐩 𝐦𝐞 𝐦𝐚𝐧𝐚𝐠𝐞 𝐚𝐧𝐝 𝐨𝐩𝐭𝐢𝐦𝐢𝐬𝐞 𝐌𝐞𝐭𝐚 𝐀𝐝𝐬 𝐚𝐬 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭𝐥𝐲 𝐚𝐧𝐝 𝐞𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞𝐥𝐲 𝐚𝐬 𝐩𝐨𝐬𝐬𝐢𝐛𝐥𝐞 for maximum results 👇 

→ Comment "𝐀𝐈" below and 𝐋𝐈𝐊𝐄 this post and I will send you a link to the GEMINI resource for FREE.

Here are some of its main features:

☑️ 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐢𝐜-𝐅𝐢𝐫𝐬𝐭 𝐂𝐚𝐦𝐩𝐚𝐢𝐠𝐧 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: I build using simplified architectures (Broad, CBO/Advantage+ Campaign Budget) to give the Meta auction the liquidity it needs to stabilize CPMs and find purchasers at scale.
Creative Strategy as Targeting: Instead of relying on fragile interest groups, I engineer "Angle Stacks" (e.g., Pain-Agitation-Solution, Feature-to-Benefit, Contrarian) where the hook and messaging act as the filter to qualify the right ICP.

☑️ 𝐑𝐚𝐩𝐢𝐝 𝐂𝐫𝐞𝐚𝐭𝐢𝐯𝐞 𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧: I provide a deterministic testing framework (FAST or DEEP modes) to identify winning hooks and visual formats early, allowing you to kill underperformers and double down on high-MER (Marketing Efficiency Ratio) assets.

☑️ 𝐃𝐢𝐫𝐞𝐜𝐭 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐞 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞: Every ad is audited against Meta’s "Personal Attributes" and "Misleading Claims" policies to prevent account flags while maintaining a high-converting, aggressive edge.

☑️ 𝐃𝐚𝐭𝐚-𝐃𝐫𝐢𝐯𝐞𝐧 𝐅𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐋𝐨𝐨𝐩𝐬: I map ad-level performance back to your specific business goals (PURCHASE, LEAD, BOOK_CALL) and provide clear iteration rules based on primary KPIs like CPAs and secondary metrics like Thumbstop Rate and Hold Rate.

Imagine being able to 𝐢𝐝𝐞𝐧𝐭𝐢𝐟𝐲 𝐭𝐡𝐞 𝐩𝐨𝐨𝐫𝐞𝐬𝐭 𝟐𝟎% 𝐨𝐟 𝐬𝐩𝐞𝐧𝐝 𝐚𝐜𝐫𝐨𝐬𝐬 𝐲𝐨𝐮𝐫 𝐞𝐧𝐭𝐢𝐫𝐞 𝐆𝐨𝐨𝐠𝐥𝐞 𝐀𝐝𝐬 𝐚𝐜𝐜𝐨𝐮𝐧𝐭 𝐰𝐢𝐭𝐡𝐢𝐧 𝟓 𝐦𝐢𝐧𝐮𝐭𝐞𝐬 (or less) and immediately being able to cut this wasted ad spend.

This is now possible, with the use of advanced AI.

⬇️ On the left of the video you can see the prompt I input into the AI. On the right of the video you can see the full output ⬇️ 

A detailed 8-page wastage report that Tiers and categorises opportunities into 4  different Tiers:

🔴 Tier 1: first 5%, really, really, really bad
🟠 Tier 2: second 5%, really, really bad
🟡 Tier 3: third 5%, really bad
🟢 Tier 4: fourth 5%, bad

→𝐋𝐢𝐤𝐞 this post & comment "𝐀𝐈" and I will send you the full prompt along with a demo of the 8-page output file (with real savings numbers but anonymised data)

📩 𝗗𝗠 𝗺𝗲 𝗶𝗳 𝘆𝗼𝘂'𝗱 𝗹𝗶𝗸𝗲 𝘁𝗼 𝘁𝗲𝘀𝘁 𝘁𝗵𝗲 𝗔𝗜 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗼𝘄𝗻 𝗯𝗿𝗮𝗻𝗱 (open to Brands only for now)

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The Battle

🌈 Neil Andrew

Jack Felstead

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The Battle

🌈 Neil Andrew

Jack Felstead

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Jack Felstead's LinkedIn Performance

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