A: Good catch. The reviews are all genuine.

The reason many reviewers only have 1-4 reviews on AppSumo is likely because a large portion of our users are discovering AppSumo for the first time through Sendpilot.

I have an audience of around 16,000 people on LinkedIn, and many of them followed the launch and purchased through AppSumo. For a lot of them, this was their first AppSumo purchase, which is why their reviewer profiles show very few previous reviews.

Another factor is our very hands-on support. I personally reach out to most new users, our support replies within minutes, and we frequently send Loom videos to help people get set up. That tends to motivate happy users to leave a review.

But there is no engagement pod, incentives, or review manipulation involved. All reviews come from real customers who purchased the product through AppSumo.

---------The LinkedIn ban risk---------

This is the bigger concern, and the answer is usually misunderstood.

LinkedIn does not detect automation tools.

LinkedIn detects behavior patterns.

Their systems look for signals such as:

• extremely fast profile visits
• sending actions too quickly
• scrolling search results rapidly
• identical message patterns
• repeated IP changes across countries
• consistently hitting weekly limits

Those are the behaviors LinkedIn associates with scrapers and spam systems.

Now here’s the ironic part:

Many people who use LinkedIn manually actually trigger these signals more often than automation users.

For example, imagine someone doing outreach manually.

They open 40 tabs, click profiles rapidly, copy-paste messages, jump between searches, and send connection requests quickly to save time.

To LinkedIn’s system, that activity looks exactly like a scraper.

Automation tools built properly do the opposite.

They slow everything down.

SendPilot introduces:

• randomized delays between actions
• natural pauses between sessions
• safe limits that stop campaigns before LinkedIn limits are reached
• location-matched proxy infrastructure so activity doesn't appear from multiple countries

In other words, the system intentionally behaves less efficiently than a human trying to rush outreach manually.

This is why many automation users actually run outreach more safely than manual operators.

3. IP and location safety

One of the easiest ways LinkedIn flags accounts is through IP inconsistencies.

Many automation platforms use shared infrastructure where users appear to be logging in from a completely different country.

For example, a user located in the US might suddenly appear active from a French data center.

LinkedIn can see that immediately.

SendPilot avoids this by matching proxy locations to the user’s real region. If you’re active on LinkedIn from your phone and using SendPilot at the same time, LinkedIn sees both activities coming from the same geographic location.

Users can also connect their accounts through their browser session, meaning activity happens through their existing LinkedIn session.

So from LinkedIn’s perspective, it simply looks like normal usage from your own device.

4. Safety thresholds

Another major red flag on LinkedIn is repeatedly hitting the maximum weekly connection limit.

That pattern signals aggressive outreach.

SendPilot automatically pauses connection requests before users reach that limit, so accounts never trigger that signal.

5. Targeting and acceptance rates

LinkedIn also evaluates how people respond to your connection requests.

If an account sends 500 requests and only 2–3% are accepted, LinkedIn interprets that as spam behavior.

Good targeting protects your account.

Higher acceptance rates signal that your outreach is relevant, not spam.

The key point

The risk isn’t automation.

The risk is behavior that looks like spam or scraping.

Most account restrictions happen because users push tools too aggressively or target the wrong audience.

Sendpilot is designed specifically to prevent those patterns rather than allowing users to push the system into risky behavior.