Measuring Social Media ROI in 8 Steps: From Dream To Reality

The importance of social media was never so high, and the resources spent on social media management are increasing correspondingly. With the increased overheads and costs, trying to attribute social media cost to the social media business impact or revenue, was never more relevant. Seems like a classic case for an ROI calculation. The problem is that measuring social media ROI is a damn difficult thing to do. In reality, it’s a challenge ANY online brand is facing. Before going into the how, it’s critical to grasp where are the challenges first.

Why Measuring Social Media ROI Is So Damn Difficult?

When you are managing your PPC campaign, it’s easy. The purpose of this campaign is to acquire new users and that’s how this campaign should be measured. When managing your social media properties, your purposes are (at least) twofold: Both users retention, (Usually your followers are existing users, which you will try to bring back to your product) and users acquisition, (Your existing customers will often share your content and will help you to acquire new users). The problem is that when you are attributing revenue to conversion and calculating user’s life time value, you are already taking into consideration the entire retention impact for this user’s life. Counting user’s retention impact, and user acquisition impact will end with counting the same revenues twice. The best practice to overcome this challenge will be to measure Social Media revenues while attributing only new users acquisition. At a later stage, make an A/B test between users who were invited to follow your brand over the social media, vs. users who were not. Measure the delta between the two groups. This delta will be the retention impact of your social media marketing.

How To Measure Social Media ROI:

  1. Make sure to publish all your links with unique tracking parameters.
  2. Make sure to save these unique tracking params in a tracking cookie located on your user’s browser.
  3. Make sure to record the tracking params recorded in the tracking cookie to your data-base at the conversion stage.
  4. Attribute revenues to acquired new customers. This will be your social media marketing impact on users acquisition.
  5. Perform the A/B test explained above and calculate your delta. This will be your social media marketing impact on users retention.
  6. Calculate total social media revenues by adding user acquisition revenues to users retention revenue.
  7. Calculate the total cost associated with your social media management.
  8. Calculate your ROI by following this formula:

    Measuring Social Media ROI

    ROI Formula

That’s it. You have finished to measure your social media ROI. Bare in mind though, that Social Media poses a value which is beyond ROI, user acquisition or user retention. It has a lot to do with fluffy concepts like brand awareness and engagement. Brand awareness and users engagement are Fluffy and intangible indeed, but business critical for sustainable brand creation. While taking that into consideration, your social media ROI will often turns out as negative. What’s important here is that you created a baseline. This baseline must demonstrate improvement constantly.

That’s all folks. I really hope it make sense to you. Let me know if you have any questions or comments. Cheers, Dada.

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How to Calculate Viral Coefficient

What viral coefficient actually is?

Product’s viral coefficient is the answer to the question “How many additional users one new user will bring organically ?” If for example Facebook found that each new user will usually bring 5 additional users by inviting his friends through email API, and 1.2 which will join because of this person is telling his friends about how wonderful Facebook is, Facebook can conclude that their product viral coefficient is 6.2.

Calculating viral coefficient
There are two methods to calculate viral coefficient. One is quite accurate, cookie tracking based but usually not feasible. The other one is based on high level estimations, but actually can work for ANY website or product. Calculating Viral Coefficient

Calculating Viral Coefficient

Method A:
Imagine only people who has invites can become your users. Imagine only existing users issue invites. Imagine that you can attribute each new user to the inviter at the individual level. Now stop imagine and look at how gmail, Quora and Pinterest started. These website (Any many others) started their service as a closed, invites only party. Besides the fact it makes the newcomers feeling prestigious, it allows these website to calculate viral coefficient in a very accurate way. Each invitation gets a unique tracking URL, hence each newcomer is necessarily coming through a unique tracking URL. It’s enough in order to calculate how many new users each existing user brought. It’s an excellent way to calculate viral coefficient. The only problem is that this method can be used only at early stages of product’s life. Usually products who like to grow, must open up their gates.

Method B:
Being realistic, most websites and most brands will serve users regardless to whether they received an invite from existing user or not. This very different situation requires a very different approach to viral coefficient calculation. Using method B, we will look at the total number of users we have and split them into two buckets. In the first bucket, we will place all users we had to bring proactively. It’s obviously includes paid efforts such as PPC or media-buy, and often includes SEO and referrals traffic if these not happened organically. The 2nd bucket will include all the rest – users that arrived virally! The proportion between the two should give us the viral coefficient, but WAIT!

One important correction will make your calculation even more accurate and much more prudent. Cookie tracking is reliable to a limited degree. As a rule of thumb 20% events are not tracked properly by the cookie. What it means is that your first bucket is actually 20% bigger then what you could measure. The second bucket is necessarily smaller than was calculated initially.

I find method B to be exciting and very pragmatic way for viral coefficient calculation. What do you think? I’m really curious to know!

P.S
When calculation viral coefficient using both methods, it’s critical to remember that it’s a variable that changes throughout the product’s life. Facebook viral coefficient today is very much different than what it used to be 5 years ago. This comment puts viral coefficient in the right perspective. Viral coefficient is a very good indicator for product’s virality, but it’s always based on historical data. Historical data often does not project the future.

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Marketing Time Attribution Problem Explained and Resolved

It often takes a while between the time we are making a marketing effort until the time these efforts makes a business impact. This time gap that creates the marketing  time attribution problem can often distort reports and can drive to wrong business decisions. In the context of internet marketing, any web analytic solution must attribute the conversion to the time in which a click occurred, or to the time in which the conversion occurred. Google products (Google Adwords, Google Analytics) for example, attribute the conversion to the time of click.

But what happens when we are taking the cost from one source (e.g: an ad-server) and the conversions from another source (e.g backend reporting tool)? How can we know how long elapsed between the click and the conversion? How can ROI be calculated when the conversion are still coming in?

This problem can be resolved to a large extent using tracking cookies. If you are a website owner that injects tracking cookies to your visitors, and this cookie records your campaign attributes, you can add to that a click time stamp. Whenever this user will visit your site again, and will make an action, you can pull the campaign attributes and the time in which the user clicked your ad. The time of the click is indicative of the time in which the cost incurred.

This way you can report cost and conversions plotted on the same timeline.
Though it will not be suitable for accounting purposes, for optimization and business decisions, it will be often much more of a precise view than the alternative. Let me know how it works!

Yours, Dada

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Internet Marketing Attribution Problem Explained

I know that the title “attribution problem” sounds intimidating or even boring but first, it’s one of the most important principals of internet marketing and second, I swear to god, it is simple to understand.
Let’s say you have a hot dog stand inside a mall and you came up with creative ways to boost up your sales.

Creative way No. 1: You found someone to handout flyers wearing a hot dot costume at the mall’s entrance.

Creative way No. 2: You placed a new sign saying “Awesome hot dogs here”.

A week later, you can definitely say that your sales went up, but you don’t know why. You do have more customers coming in, but you don’t know whether it  because of the hot dog guy, or because of the new sign. We will call that source attribution problem and the asense of that is that we can not attribute new business to acquisition source.

Cause you so damn clever, you decided to write a coupon code on the flyers the hot dog guy is handing out. This way, when a new customer is dropping by, he is likely to show you his flyer and you will know that he was the acquisition source.

Another week later, once you solved the source attribution problem you found out that the sign didn’t bring any new customers even though it was a costly marketing efforts for you.
Without further dues, you stoped paying for the sign, and you tried to figure out whether or not to continue with the hot dog guy. Even though it does drive sales, it was costly (Warning: Attention required). You paid the hot dog guy $1000 during previous month, and he generated only $700 of operational yield (What you actually earned, deducting the cost of the hot dog itself). Based on that calculation, you halted hot dog guy marketing but than something unexpected happened.

Customers with coupon codes kept arriving. At the first few days, there were many, and later there were few. When you re-did you calculation, you noticed that actually there were $1200 worth of sales attributed to the hot dog guy. You understood you did a mistake. You attributed the cost and the revenues of the hot dog guy to the same month, even though the revenues kept  growing while the cost remained the same. This problem will be referred as time attribution.

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Best Internet marketing tip

So I know it sounds pretensions but I truly believe I’m about to share with you the best internet marketing tip out there. You can spend hours reading internet marketing blogs, browsing through blackhat forums or hiring a social media expert. You can go to conventions or even take online courses, but there is one internet marketing tip that there are only few which are brave enough to share.

internet_marketing_tip no one know's shit

OK, I know it doesn’t come across as the most constructive piece of advise but it is and I’ll explain. In this allegedly perfect market called “The Internet”  there’s allegedly perfect competition, in which everything is known and everybody have the same access to resource. In these conditions, no one can earn a significant amount of money or at least to operate in high margins.

To a degree this is true, especially when running around the most popular online forums and competing with all the others in the same game, but in reality, pockets of profitability will always be found, regardless if it’s inbound marketing or paid marketing.

And now I’m getting to the point.

In reality no one knows anything, you must experiment all the time, and to make sure you have the ability to attribute the success or failure of every effort.

The cost and revenue of each and every marketing effort, suppose to be measured. Based on ROI, whatever effort which is working should be expanded, and whatever activity which is not, should be optimized or eradicated.

So to wrap-up this post, no one know more than you, and if someone does, he will not tell you that. Experiment everything, but before experimenting, make sure you know how to measure your success. Get your numbers right and make quick decisions.

Does it make sense?

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