Tag Archives: life time value

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

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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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Calculating Customer Lifetime Value

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Calculating Customer Lifetime Value (CLV) also known as User Lifetime Value (LTV) is an internet marketing basic skill. While there are many ways to calculate customer lifetime value, few principles always must be followed. How to calculate customer’s LTV? Here’s how.

First, let’s define what Customer Lifetime Value is. Customer Lifetime Value is the entire customer contribution throughout his life to the bottom line, after deducting cost of acquisition and cost to serve.

calculating lifetime value.clv.ltv.calculation

Lifetime Value Calculation: Customer Contribution

The customer’s contribution is all the earnings coming from this customer during his “life”. But what customer’s life actually is? While it’s easy to define the birth of a customer (Usually the first payment made by the customer. Might also be the event of user registration. Anyhow, the birth of a customer should correlate to the definition of conversion), it becomes much more difficult to define the “death” of a customer. Defining churn is difficult since the customer usually does not inform us that he churned. What usually solve this problem is looking at a group of customers and to measure their contribution during different stages of their life. This technic called cohort and will often give us a pattern that looks like this:

calculating lifetime value.clv.ltv.calculation.graph

In the above example, it’s clear that majority of the contribution occurs right after the conversion. There is however long and significant cohort long-tail. It’s quite clear it makes limited sense to measure LTV for over the age of 20 weeks.

Lifetime Value Calculation: Cost of Acquisition

The cost of acquisition, also known as CPA, is the variable cost associated to bringing this particular user. If this user was acquired through Adwords campaign, it will be the cost of media. If the acquisition stem from sales guy efforts, the cost of this guy need to be recorded as the CPA.

Lifetime Value Calculation: Cost to Serve

From all 3, the concept of cost to serve is the most illusive one. It’s basically the variable cost of serving this particular customer. If you are not familiar with the term variable cost think about it this way; what cost would have been saved if you didn’t have to serve this particular customer? It might be the shipment to his home address. It might be the Christmas greeting card. It might be the cost of speaking to him an hour every week. (Though some will refer the later as fixed or semi-fixed costs since its covered by a fixed salary).

Lifetime Value Calculation: Real Life Example

The stage is yours! Share your real life examples or questions in the comments below. Help is promised.

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How to Calculate Viral Coefficient

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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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How to Define a Web Conversion

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You know, the first things one should do when flipping a lame business into a successful one, is to create business definitions. The beauty about business definitions is that it helps you know what you count when you count. In addition, it makes sure you count the same thing every time you count it. That’s a perquisite for creating a baseline, that shows where things are at, which is a starting point for any optimization process. What does it have to do with web conversions?

A conversion is a type of business definition, indicating an event in a user life-cycle. A series of such events, leading to a desired action is called a funnel. While often there are several types of conversions, when acquiring new customers it usually make sense to focus on one specific event. This specific conversion should be the event in the user’s life which is likely to indicate about his future behavior. It often might be registration of a user, user’s first deposit, user’s submission of a sales lead, etc.

Once you have this solid definition of web conversion, you can start calculating your conversion rate. Conversion rate is the chance that a person arrived to your website will make a web conversion and is equal to #Conversion divided by#page-views. After you reached an understanding of what is your current conversion rate, you can start think of ways making it even better (Anyone said a-b testing?)

Defining a web conversion enables another critical capability besides optimizing your conversion rate. It allows to associate revenues with conversions and to attribute revenues to a conversion (The singular form was chosen on purpose. It’s important to be able linking revenue to a specific user).

For example, if your website generated 1,000 new users and these users will deposit throughout their life $1,000, each user worth to you $1. If a registered customer is likely to deposit, it make sense to acquire registrations of customers and to attribute revenues to the event of registration. Your user’s value, or user’s lifetime value equals $1. To simplify things, it’s important to attribute users’ lifetime value (LTV) to the acquired acquisition and not to any other type of conversions, otherwise you might find yourself counting the same money twice.

Understanding LTV is nice in many ways, but it’s critical in three main ones:

- Be able to project  your cash-flow: Once you know how many users you have, and once you can project how they will behave, you can start projecting your cash-flow.

- Understand how much you will be willing to pay for a conversion: If your LTV for registration is $1, and you want to earn money, than you will need to pay less than $1 for a new registration. If your cost per acquisition (CPA) is $0.5 and your LTV is $1, for each acquired customer you earn $0.5.

- Increase your LTV:  Once you know what is your LTV and you have a baseline for that, you can start playing around with cool ideas expected to increase your earnings for each acquired customer. You can’t really do that beforehand!

Well folks, that’s not all, but that’s all for today. Soon I’ll be writing about LTV calculations, a/b testing, and few more exciting topics. In the meantime, let me know if it make sense to you.

Cheers, Dada

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