I spent US$50 on Reddit Advertising as an experiment

[eyrion]

I decided to give Reddit Ads a try, despite seeing some sentiment here that advertising doesnt work. I figured I could specifically target the communities that would be interested in my product, and limit to the countries I already have subscribers. Well long story short it didn'`t work.

• 77,902 impressions at $0.70 eCPM
  
• 225 clicks at $0.26 CPC
  
• Only 113 clicks show up in my access logs
  
• Only 7 clicks browsed past the landing page
  
• Zero sign ups
  
• Zero subscriptions

I realise this was a small sample, and only ran just over a week, but to have basically no return at all on a product which starts at $2.50USD means paid advertising will likely never work for my SaaS.

I also have no idea why there were twice as many clicks as I have evidence for.

(teslemetry.com)

 

[dianad373]

@eyrion in my experience reddit has the worst ad platform. The clients are damn near fraudulent. When I advertised on reddit the avg time spent on my page was like .1 seconds, pointing to the fact that most ad clicks are misclicks.

 

[beclaire37]

@dianad373 I don't think it's misclick as much as it's users thinking it's an actual reddit post. There are ways to alleviate this and make it less jarring for the user.

 

[ryanc]

@eyrion Have you tested the same AD on Meta before going to Reddit? Because there's no better place than advertising first on Meta, then going to others, not just because of the target audience, but as well to see if your AD really works or not.
Also, depending on your SaaS, is it for customers or B2B, both or where you think your niche is? I need to think about that.
I hope you re-run on Meta, provide us with feedback then probably you can go on other platforms, 50$+ is a good start to validate, but I think you just failed in the platform audience I must say.
Good luck on the next run

 

[eyrion]

@ryanc No but its a good idea. I'm B2C and I know my niche, there are certain Facebook groups that are my exact target audience.

 

[sax_mad]

@eyrion Please remember this. No matter which platform you run ad on, they have an initial learning phase where their algorithms try to understand your ad, product/service, targeting settings, and optimize delivery. This learning phase typically takes around 1-2 weeks.

Hence, we always ensure that testing is done for at least two weeks with enough ad spend during those two weeks to have decent amount of data to derive insights.

 

[eyrion]

@sax_mad That basically prices me out of the advertising market, which is basically what this experiment has confirmed for me. I somewhat expect this early on given how cheap my product is.

 

[jonmichael818]

@sax_mad Thanks for the insight.

 

[mrrunningfish]

@sax_mad Agree with your thoughts, same goes when I tried fb ads, but just only tried for 2 months. Worked well so I didn't spend again.

 

[mdfan13]

@sax_mad How would you define as "enough ad spend?" I'm thinking of running a small FB/google ad campaign to validate an idea but not sure how much to spend. Would $10/day for 2 weeks be reasonable?

 

[sax_mad]

@mdfan13 When deciding the budget for an ad campaign during the initial learning phase (typically the first two weeks), there are a few key factors to consider:

1. Conversion Estimates: If the ad platform provides estimates for conversions based on your budget, it is generally advisable to start with a budget that aligns with your desired conversion goals. This approach allows you to set expectations and gauge the campaign's performance from the outset.
2. Traffic Estimates: If the platform only provides traffic estimates, you'll need to factor in industry benchmarks for conversion rates within your specific niche or vertical. By combining the estimated traffic with a reasonable conversion rate assumption, you can estimate the potential conversions and adjust your budget accordingly.
3. Testing and Optimization: During the learning phase, it's crucial to allocate a portion of your budget for testing different ad creatives, targeting options, and other variables. This experimentation will help you identify the most effective strategies and refine your approach as you move beyond the initial phase. But dont disturb the learning phase by making any edits to the campaign.
4. Budget Flexibility: It's generally recommended to start with a conservative budget during the learning phase, as this allows you to evaluate the campaign's performance and make data-driven decisions before scaling up your investment. However, ensure that the budget is sufficient to generate a statistically significant amount of data for analysis.
5. Campaign Goals and KPIs: Align your budget with your overall campaign goals and key performance indicators (KPIs). If your primary objective is to drive conversions, allocate a larger portion of the budget towards high-intent audiences and placements. If your goal is brand awareness or reach, you may need to distribute the budget more broadly across different targeting options.

Remember, the learning phase is an iterative process. Continuously monitor your campaign's performance, analyze the data, and make adjustments to your budget, targeting, and creatives as after campaign is exited the learning phase). By taking a data-driven approach and remaining flexible, you can optimize your ad campaigns for better results and a higher return on investment (ROI).

 

[kchorne]

@eyrion With a ACV that low, you’re really going to struggle with getting paid ads to work … I’ve never seen it done

So you’re options are:
- Rely on free/lower cost channels (content marketing, SEO, product vitality)
- Raise your prices