TL:DR; 5 Step process

• Feedback  →  tells you what’s wrong  →   Use Formiva to create forms quickly
• Testing  →  validates what actually  works  →  Use Insighter to run a/b tests to see what works  
• Competitors  →  help you track positioning, pricing, and market saturation  →  Use Lurk to check competitor pricing.  
• Retargeting ads  →  keep your brand familiar before people are ready to buy   →   Choose Awareness in facebook as goal & google
• Email  →  helps you retarget, recover lost visitors, and build loyalty  →  Use Emailwish to automatically setup exact email flows I used to generate $150.8k from email. ( don’t let its low rating fool you, it’ works well)

 

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Background

I was one of those fools who thought  dropshipping was luck

Find a winning product, scale to the moon, buy a Lambo. Simple.

That was the dream lol, but reality was very different.

Most of my stores failed. Ads, Shopify fees, and dozens of apps slowly drained money while I kept chasing “winning products” and following generic guru advice.

Eventually I realized most of the advice was just recycled theories made to sell courses.

Ads and demand still matter, but after a point you need to stop relying on generic advice and start understanding why people actually buy.

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1. Stage 1 (~2 minute ) : Fixed my ads (based on real objections)

So instead of guessing, I started asking.

Added a short flow before/after purchase with questions like:

• what made you click this ad?
• what almost stopped you from buying?
• what were you looking for?

Nothing fancy, but the answers gave me real insights.

If you are unsure on what kind of questions to ask, just use something like Formiva. It has great templates to get you started. 
Offer a small incentive like a discount to get engagement.

From the data i collected, I realized people kept saying:

“not sure if this works” That made me realize my ads lacked trust.

So I started showing ads with:

• UGC
• before/after
• proof-based ads

Simple changes based on actual feedback, not theories.

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2. Stage 2 (~2 minute ): Fixed my product page through testing

A lot of people said:

“shipping feels too long”

So I didn’t touch the price, I didn’t optimize ads, I tested a few UI design changes. 

• made delivery timelines clear above the fold
• added “arrives by”
• reviews position

Small changes, nothing ground breaking which increased checkout rate from ~0.9% to ~1.4%.

Used a simple A/B testing app to run clean tests without messing data. Many different A/B Testing apps in the market but I found insighter, with most relaxed limits in the free plan.

New apps generally have very good limits in the free plan and that’s the best time to use them ;)

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3. Stage 3 (~1 minute ): Started keeping a tab on my competitor pricing.

This one sounds obvious now, but I used to constantly check competitor stores for pricing manually every other day.

Eventually I just set up competitor tracking on Lurk  and enabled alerts instead. There are many apps out there, this was the only one I found with real time alerts included in the free plan.

Way less mental overhead and honestly, it helped more with positioning than copying prices

A few times competitors started pushing aggressive discounts, so instead of joining a race to the bottom, I changed the ad angle and emphasized quality and reviews instead.

And when margins became too thin, I moved on before wasting more money on ads.

Honestly, competitor tracking is one of the easiest ways to understand when a market is becoming saturated.

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4. Stage 4  (5 ~ 10 minute ) : Fixed retargeting

Most people don’t buy on the first visit. That’s normal.

But a lot of stores either ignore retargeting or run it poorly.

I know showing ads 10–11 times can get expensive, but that’s why retargeting ads on facebook and google should usually be impression/awarness-based, not conversion-based. Your ads were already optimized for conversions the first time, no need to optimize it again while retargeting.

Awareness based ads are generally much cheaper than conversion based ads. This will help you bring your conversion rate from 1.4~1.5% to easily  2~ 2.2%

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5. Stage 5  (30 sec ~ 1 minute ) : Retargeting & Improving brand loyalty (through emails)

Once you are done with retargeting ads, you need a cheaper and more scalable way to keep reaching those users and that is through email !!

Most people think email marketing means blasting campaigns to purchased lists. That’s usually where stores go wrong.

The real value comes from automated emails (flows) triggered by user behavior:

• Welcome Series→ introduce your brand and build trust
• Abandoned cart Series→ recover lost checkouts
• Review request Series→ build social proof for future buyers
• Post-purchase Series→ increase repeat purchases and loyalty

There are many more flows but these are enough to get you started. For email marketing, there are quite a few apps but If you don’t want to write any emails and get started with essential flows I will recommend   Emailwish ( don’t let its low rating fool you, it’ works well) 

Emails will help you increase your conversion rate from ~2.2 % to around 2.8% ~ 3%

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Over time, I realized the stores performing best weren’t just running ads better.

They had better systems. Miss one part of the system, and results become unpredictable.

To summarize 

• Feedback  →  tells you what’s wrong  →   Use Formiva to create forms quickly
• Testing  →  validates what actually  works  →  Use Insighter to run a/b tests to see what works  
• Competitors  →  help you track positioning, pricing, and market saturation  →  Use Lurk to check competitor pricing.  
• Retargeting Ads  →  keep your brand familiar before people are ready to buy   →   Choose Awareness in facebook as goal & google
• Email  →  helps you retarget, recover lost visitors, and build loyalty  →  Use Emailwish to automatically setup exact email flows I used to generate $150.8k from email. Despite it's poor rating, it works

Built an adaptive MTA operations & deliverability platform focused on automation first, while still keeping every layer configurable.

Features include:

• Automated bounce intelligence with pattern-based classification, throttling, suppression, retries, and provider-aware actions
• Dynamic IP warmup engine with growth/decay logic based on real delivery utilization and deferral signals
• Adaptive throttling/backoff that reacts to ISP behavior, temporary blocks, complaint spikes, and rate limits in real time
• Automated IP pool reputation management with scoring, promotion/demotion rules, and pool isolation
• ISP intelligence dashboards with provider-level delivery, bounce, and defer analytics
• Traffic shaping, routing, and queue orchestration across domains, IPs, and providers
• Multi-tenant ESP operations tooling with centralized monitoring, logging, and policy control
• Fully configurable override system, every automated decision can still be manually tuned when needed

The goal was to reduce manual operational overhead while still giving deliverability teams full control over infrastructure behavior.

Do you think you would be interested in something like this?

Hi guys, over the last couple of years, we ended up building our own MTA management layer focused on deliverability, reputation recovery, IP warmup, ISP-specific throttling, and automated traffic routing.

The easiest way to describe it is probably: imagine a PMTA console manager on 100x steroids.

Right now we’re still relatively small, handling roughly around a million emails, but the system has been performing surprisingly well for us, especially compared to the amount of manual work we used to do before.

The interesting part is that most of the logic is fully automated. Instead of static rules and fixed warmup schedules, the system continuously reacts to ISP behavior, bounce spikes, throttling patterns, and reputation signals in real time.

We’ve been considering whether there would actually be interest in this kind of system if we cleaned it up properly. Potentially open-sourcing parts of it, while maybe offering a paid hosted/enterprise version later on.

Some of the things it currently handles:

1. Smart IP Warmup

When you get a new IP address, you cannot send 1 million emails on the first day. You have to "warm it up" so providers like Gmail or Yahoo trust you.

• Per ISP: Gmail, Yahoo, Outlook, etc. are all warmed separately because each provider behaves differently.
• Success-Based Scaling: Instead of blindly increasing volume every day, limits only increase if delivery health remains good and a minimum % of capacity was utilized.
• Automatic Decay Handling: If traffic stops for a few days, the system slows things back down automatically to safely re-warm the IP.

2. Bounce-Based Actions

A bounce is when an email cannot be delivered, which hurts sender reputation.

The system monitors bounce/error patterns continuously and reacts automatically:

• Throttle: Slow down sending to a provider
• Suspend: Pause sending temporarily if errors become serious
• Redirect: Shift traffic to safer IPs while recovery happens.

3. Reputation-Based IP Pools

Not all IPs are treated equally.

• High Reputation Pool: Reserved for the cleanest traffic/senders
• Warmup Pool: For newer IPs still building trust
• Recovery Pool: For IPs that need slower traffic and recovery time

The main goal was basically to build a more self-healing infrastructure where the MTA layer can make intelligent decisions automatically instead of relying on constant manual intervention.

We’ve been debating whether it makes more sense to:

• Open-source it: potentially build reputation in the email infrastructure space, contribute something useful to the community, and hopefully bring in clients for our main business.
• License/self-host it: similar to enterprise infrastructure software, where companies can run it themselves while creating an additional revenue stream for us.
• Offer a hosted enterprise version: where we manage the infrastructure layer entirely.

What people running serious email infrastructure would prefer?