Market Intelligence Tools

[WMD]

Hi,

I'm in the process of starting an online business. Specifically to sell products.

I need some opinions on these market intelligence tools that claim to have a formula for determining product profitability (which I take with a pinch of salt):

JungleScout
Viral Launch
Helium 10

There are more similar tools out there, but they all seem to be heavily focused on Amazon's sales data.

I am sceptical about these tools, so I will be relying on this data to a certain extent. I will incorporate findings from other forms of market research.

Now if you were to start an e-commerce business, would you consider using these tools and if so, to what extent? Is the data they provide useful or is it all a gimmick? Wanted to hear opinions from actual entrepreneurs as opposed to reading online reviews that aim to promote them.

 

[fisicx]

Those tools might give you relative profitability between products but that’s about it.

Your profit depends on the product, the competition, marketing costs, desirability and everything else.

 

[Fagin2021]

People are sick of hearing me say this, but I'll say it again anyway...

Automation complements human judgement - it's not a substitute for it.

 

[UKSBD]

People are sick of hearing me say this, but I'll say it again anyway...

Automation complements human judgement - it's not a substitute for it.

Yes, but stats and data can trump human judgement.

You might be convinced that something is true, but if all reliable stats and data (gained via automation) tell you the opposite, what do you believe, your human judgement or the stats?

 

[Fagin2021]

Yes, but stats and data can trump human judgement.

You might be convinced that something is true, but if all reliable stats and data (gained via automation) tell you the opposite, what do you believe, your human judgement or the stats?

Exactly my point. It's not an either/or. Data can give you the stats, but it's often pretty poor at interpreting them. Here's an example....

A while ago I ran an Ads Campaign where analysis showed that almost all conversions happened in the evening, but most clicks took place during the day. 'Data' implied that we could reduce costs and improve performance by 'day parting' the ads - fewer in the day, more in the evening.

Further investigation revealed that buyers typically searched on their mobiles on their way to, or at work, but converted on their desktops when they got home.

The data alone could have led to a disastrous conclusion.