Justin Cooke

March 25, 2013

Today’s guest post is from Mark Collier and focuses on the data and analysis of sites sold on Flippa.  While some of the points aren’t necessarily ground-breaking news, I LOVE the fact that his findings here are based on hard data and reinforce some of the things we’ve thought about the value of site sales.  I had some questions about the analysis and will lay them out in the comments below…we’re interested in hearing your thoughts as well!  Now enough from me…over to Mark.

I’ve only ever sold one website but I do know a thing or two about data analysis.

I’ve been gathering data on Flippa sales for the last few months and have recently published a comprehensive analysis of this data.

I wanted to share the major findings of my study here, which focused on the influencers affecting the price of a website.

The study

It turns out that website values are fairly predictable and the market for websites is pretty efficient.

I analysed 52 factors I felt might impact the value of a website for 6,500+ sales on Flippa.

Using a data analysis technique known as multiple regression I created a model that would predict 68% of the variation in website prices.

This model indicates which factors are statistically significant influencers of the website price and how much influence they have.

Revenue, profit and traffic

Beyond any shadow of a doubt revenue, profit and traffic are the three most important factors influencing the sale price of a website.

If you cut costs by $1 dollar per month without impacting service (and thus increase profit) the value of the website increases by $3.50.

If you increase revenue without impacting other metrics like traffic e.g. by adjusting some sales copy each extra $1 earned per month will add approx. $2 to the sale price.

Similarly increasing sustainable traffic has a substantial impact on the value of the website.

To this end verifying you traffic by linking your Google Analytics account to Flippa will on average see a $630 increase in the website’s sale price.

Interestingly, having an unverified Google Analytics attachment has little or no bearing on the sale price.

Upgrades

Buying premium upgrades on Flippa is probably one of the best investments you will ever make.

All the tested upgrades; highlighted, screenshot, bold and premium listings are significant influencers.

This makes good common sense as getting attention in a crowded market is tough.

Each of the low cost upgrades mentioned will typically increase the sale price by approx. $500.

Even assuming a large margin of error the returns to your $5-20 investment will likely be in the thousands of percent.

While there wasn’t a lot of data for premium listings, the available data suggested the $200 upgrade would add between $6,500 to $10,000 to the sale price, although I would like to see some further testing of this conclusion.

My advice

I’m not a website flipping expert but I believe that this data is exceptionally informative for website flippers and that implementing from the actionable data will lead to substantial profits.

The two things that are clear from this study are:

  1. A small number of core metrics; profit, revenue and traffic are the fundamental drivers of a website’s sale price.
  2. Buying upgrades is an exceptionally effective way to artificially boost a website’s sale price.

So how do you implement from this data if your buying and selling websites for a living?

Simple.

When you take over a website, implement a laser-like focus on increasing revenue and profits.

Forget long-term strategies like SEO or content marketing, you’re flipping websites so you need quick, sustainable wins.

Redesigning the site, unless it’s set in the 1990’s is unlikely to be of significant short-term benefit.

Let the end-user of the site focus on these issues.

Primarily you should be focussed on cutting costs and increasing revenue.

Implementing new revenue streams or more aggressive monetization strategies would be my first port of call.

Product launches, email marketing campaigns and more advertising space are all good ideas but you’ll be better at knowing what works in this regard than me.

As an aside – the model showed no preference by buyers towards any particular source of revenue, advertising, affiliate or product sales dollars were all equal in the buyers eye’s.

Become a conversion rate optimization expert – testing sales pages, advertising positioning, sales copy, etc. can lead to big wins with no increased cost.

Additionally you can apply the same techniques to every website you flip and thus have an easy win every time.

I would review every cost a website has and see if you can minimize it.

Do you need the deluxe package, is there a cheaper email marketing software available, etc.

But the big wins will be found by being audacious.

For some reason people are afraid to ask for discounts. Make it your policy to call every supplier and renegotiate the price you pay.

In launching my own new business I’ve been able to make massive savings. In fact I’ve reduced my monthly costs on the order of $5,000 just by making that call.

And, of course, buy those upgrades.

I’m launching a new software product aimed at providing premium data on 150,000 daily expiring domains. Unlike my competitors I offer key data like exact match search volume so you can determine which domains are worth developing and which aren’t. I’ll be posting more data about Flippa and the domain name market on my newly launched blog.

Note: We’ve released our own website marketplace if you want to see what we have for sale.


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Discussion
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  1. Dave Starr says:

    Really good stuff. I have watched this en dof the business for years and have always marveled at the lack of actual business skills and analysis that has been incorporated. We have all these geniuses out there with MBA’s and other business smarts and yet most of the buy and sell websites business still flies strictly by the seat of its pants;

    Thanks for teaching me something while keeping it lean, mean and interesting.

    And another vote of thanks for the font. Stick with the black on white. So many artsy-fartsy guys have these gray on gray color schemes and they are very hard to read for “old farts” like me.

  2. Hey guys you know me, useless in this arena, but interesting article.

    I do want to point out how much easier and nicer to read due the layout of the new site and font, etc. is from a Content Marketing point of view.

    Good work.

  3. Interesting research, Mark!

    Of course different people have different focus, so let me say I’m into buying established website with revenue.

    I checked the full analysis post and I wish you can exclude all the turnkey-type websites that are bringing the transaction values so low…. in particularly I wonder how would that impact this:
    “The typical Flippa listing will fetch 17 times it’s starting price.”

    Are you planning on releasing more data from this research?

    Thanks!

    • Mark Collier says:

      I just took a look at the numbers and excluded websites that sold for less than $1000, it turns out that the median which in this case is the best measure of the typical Flippa listing that sells for $1000 or more will fetch 43 times it’s starting price. Interestingly 35% of websites in this category start their listing at $1.

      In terms of the regression analysis the results would be the same even if I remove the turnkey websites.

      If you have any other interesting tests you’d like me to do let me know.

      • JustinWCooke says:

        You bring up an interesting point, Mark. Is there a way to specifically look at those that start at $1 with No Reserve Vs. those that start at around 10x their monthly profit or more? I’d be interested to see if the $1 No Reserve typically sells for more than those that start at 10x (Due to the Most Active section, followers/watchers, etc.) I believe that’s the case but, of course, would be better to know with hard data, eh?

        • Mark Collier says:

          I couldn’t gather data on whether the listing had a reserve or not, but I could test based purely on starting price.

          I would imagine most $1 listings don’t have a reserve, would that kind of test be of interest?

        • Mark Collier says:

          Ok so I tested a few things using regression and overall the data isn’t very clear suggesting that the starting price isn’t that important.

          Setting the starting price at $1 is not a statistically significant influencer of price but it’s not far off. If the significance level was slightly better you could expect the price of a website to jump substantially when you set the starting price at $1 but I can’t recommend this concretely due to the lack of statistical significance.

          Contrary to this is the fact that as the starting price rises so does the sale price even when you hold all other variables constant.

          It may the case that a $1 starting price is a special case that draws interest and for most other cases an increase in the starting price leads to higher sale prices.

          Interestingly when I looked at listings which had to be relisted because a buyer failed to pay, there was a very moderate relationship between increasing the starting price and a final increase in the sale price as compared with the previous listing.

          You could argue that original interest garnered due to a low starting price other than $1 tends to add little to the final price because these bidders won’t be in the shake-up when the auction comes to an end but that by setting a low starting price you remove the auction from the eyeballs of individuals who specifically look for higher priced listings because they are serious buyers of these listings.

          Alternatively you could argue it’s a case of buyer psychology, by setting the starting price relatively low you seed an idea into the buyer’s mind of a lower upper bidding limit than they may have been willing to go to with a higher starting price.

          Overall I think you could find justification of either courses of action and that in truth the starting price isn’t particularly important.

          I think it would be interesting to see the effect of a reserve on the sale price as I suspect that setting a reserve has a significant negative impact on the final sale price.

      • Many thanks Mark!

        I’m curios about a parameter: the Google PageRank.

        Do you have it in your list?

        How is the PR impacting the selling price of a website?

        Thanks! :)

  4. JustinWCooke says:

    Thanks for the post, Mark! Even if less “revealing”…hard data is always helpful if it only reinforces some of the things you already “thought” about the particular issue. I am left with a few questions and am interested in your thoughts:

    1. Upgrades – Are you sure it’s not a correlation/causation issue here? Couldn’t it be that the top-dollar sites include the upgrades, simply because it’s such a low % of the overall sales price that they might as well?
    2. You mention a re-design as not being one of the quickest wins when it comes to a buy/sell flip – I understand traffic/revenue as being a bigger influencer, but aren’t there buyers who prefer a “sexy” site, pushing up the value, all other things being equal?

    I like your insights regarding content/SEO not being worth it for a quick flip. It seems to me that your efforts are better focused on trying to find a profitable paid-traffic strategy in the short-term. I wonder where that short-term/long-term value line is at though, eh?

    • Mark Collier says:

      Hey Justin,

      Thanks for having me.

      1. No regression holds all other variables constant, that means that from the regression analysis you are saying that if you held revenue, traffic, profit, etc. constant what would the effect be on the sale price if if you used an upgrade. So long as top-dollar sites are represented by metrics such as profit and revenue the results can be deemed causal and the level of increase in the sale price accurate.

      In saying that in my model there’s what’s called a constant of regression, it penalises sites of no value, so a site with zero value will not sell just because you use an upgrade because according to the model it has negative value which essentially it does.

      Upgrades would help a website overcome this constant but if the site has little value itself then it won’t reach the required threshold.

      Thus only websites that you are expecting to sell for upwards of $500 will benefit from the upgrades.

      2. Yes, the re-design was just an example of what based on the data is probably a low return on investment move.

      It is possible and likely that the 52 metrics analysed didn’t represent the quality of design so it is possible that this would influence price.

      But you could take another example. Being an fairly knowledgeable about SEO, I know that the returns to great SEO tend to be long term and there’s nothing in the data to suggest that buyers reward good SEO work despite having numerous SEO related metrics, they only reward it’s results which in short-term and most likely the flipping period won’t be realised, thus you could say that long-term SEO works are low return uses of time when flipping.

      3. I would say the short-term strategies that work well would be something like conversion rate optimization, increased monetization, better utilization of existing audiences such as email lists, Twitter, Facebook etc. essentially getting more revenue and profit out of existing resources all of which are sustainable but have an impact immediately.

      • Hey Mark,

        Great research. I haven’t heard someone talk about regression analysis since my Quantitative Methods class in Business school. Good stuff!

        I would have to agree though with Justin, though. Buyers are VERY interested in site design. You have to wrap this site in a package to make it look nice and pretty. It’s no different than selling a house to a real estate investor. The less they have to do the better.

        Heck, I’ve even had sites go for a lower price that had great conversions but lacked the “pop” that other sites had. Its unfortunate, but not every buyer on Flippa is a seasoned investor. In fact, I would venture to say that more and more buyers at most levels are newer and less seasoned.

        I do love your approach, but I think that we need to combine both the regression analysis with practical experience in dealing with buyers on Flippa. The scientific approach can only take you so far.

        Just my thoughts!

        Thanks,

        Mark Santiago, MBA
        FlippinCrusher.com

        • JustinWCooke says:

          Thanks for the comment, Mark S.

          While we’re on the subject of site design…we’re currently going through the steps of a full-on “launch” of IntelliTheme with a bunch of affiliates, an affiliate manager, etc. He said one of the downsides is that the theme doesn’t “look” as nice. It’s likely going to be one of our barriers on the sale. It’s particularly funny because we’ve tried nicer looking designs…they just didn’t earn as much! heh

        • Mark Collier says:

          Hey Mark,

          I completely agree, obviously my design example was born out of the data solely as I have no expertise in flipping but when you combine the data with the experience you reach a powerful state.

          Glad to hear I brought you back to school :)

          • Mark C.,

            Totally understand on the data. And I do love the data, so I appreciate you diving into this stuff. We need more of that in this industry if we’re ever going to really take off and become a professional market (not just Flippa), but buying and selling websites in general.

            Looking forward to your project (signed up for the early bird)…

            Thanks,

            Mark Santiago, MBA
            FlippinCrusher.com

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