Revenue sharing is one of the oldest methods of earning profits, actually, I believe it may just be right up there with trading of goods and food. For those of you not in the know, I’ll explain what revenue sharing is:

  1. A content provider wishes to distribute a certain type of content – charging for it.
  2. The content provider has not ability to charge the consumers directly, thus he partners with another party – the transport maintainer.
  3. The transport maintainer charges the consumer, while keeping a certain percentage in his pocket.
  4. Everybody’s is happy.

In general, this model works really well in many markets – specifically those that are driven by unique content – for example the mobile content market (ringtones, screen savers, games, apps) – the Apple App store is a wonderful example of how this works.

In the telecom industry, the revenue shares business is very common – however, in many cases it is highly guarded as a secret – main reason is that now one wants anybody else to know how they do it. This hiding of information, usually results in some problems – as when there is hiding of information, only those in the know are able to access it. Those in the know are called “mediators” or in Herbew “Machers”. In this entire ordeal, the mediator also takes a small percentage – leaving the content provider with slightly less. So, now it looks like this:

  1. A content provider wishes to distribute a certain type of content – charging for it.
  2. The content provider has not ability to charge the consumers directly, thus he contacts a mediator to find him a transport partner.
  3. The mediator engages the prospective transport maintainer.
  4. The transport maintainer charges the consumer, while keeping a certain percentage in his pocket and passing some funds to the mediator as well.
  5. Everybody’s is happy.

So, if everybody’s so happy – why am I bitching about it? very simple – people are Greedy and always want more – putting the entire model into a frenzy. In order to give an example, let’s imagine the following scenario:

  1. Company A provides IVR based content utilizing Asterisk server, connected to the internet.
  2. The mediator engages a premium number company, getting the total revenue of 0.08$ for every inbound minute of traffic.
  3. The premium number company leaves 0.01$ in its pocket and also pays the mediator a fee of 0.01$ per minute.
  4. The content provider gets 0.06$ of the 0.08$ – 75% of the net profit goes to the content provider.
  5. Content provider says: “Hell, I want the mediators 0.01$ as well, and I think the premium company should only get 0.005$, so I would get 0.075$ at the end”
  6. Content provider contacts the premium provider and starts complaining
  7. Premium provider negotiates and strikes a deal for 0.07 to the content provider, leaving the premium provider with 0.005$ and the mediator with 0.005$
  8. Premium provider says: “I’m not making enough money on this, actually, I’m loosing money – I’ll find a better alternative service for that access number”
  9. Premium provider asks mediator to bring in a new customer, providing similar content – mediator has sure incentive here
  10. Premium provider gets new customer and transfers the access number to the new customer – returning back to previous profits
  11. Original content provider is left with no profits and only greed in his hands
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Over the past 10 years, I’ve seen this vicious cycle happen over and over and over again, in various formats and scenarios – but always ending in the same outcome – the content provider always suffers. If you’re a content provider and you provide IVR based services, let the people that provide you the access make their cut and the people in the middle, without them, you will have a service with no access – which means no service at all. Don’t go about thinking you can keep all the profits to yourself, you will break the equilibrium of this business, and eventually, no one will want to do business with you.

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“Oh, just get me the CDR‘s and I’ll take it from there” – how many times have I heard these words before? I can’t even imagine the number of times in the past 15 years of IT/Telecom’s work that I’ve done and in the last 8 years of Asterisk in particular – when it comes to billing and fraud management, it would appear that the CDR’s are the Rosetta Stone of the industry.

Over the past 6 months, several of my friends and I had been asking ourselves this question: “Is there more to billing, fraud management and profit leakage? does it really all begins and ends with the CDRs?” – so, here we were, a group of 3 engineers dealing with telecom system and billing systems – we knew that the answer is a definite YES, however, how come most companies and system aren’t even aware of this, in such a way that causes them to leak telecom profits and waste their hard earned profit margins on simple accidental mis-interpretation of CDR records.

So, we’ve decided to sit down and start analyzing calls in real-time, trying to evaluate not only the CDR record that is received upon the completion of the call – but also understand the traversal path of the call, analyzing it in real time and evaluating it profit leakage potential. At the mean time, we’re concentrating our work on Asterisk, as it is the simplest for us to implement – however, we’re not focusing it only on that – we’ll looking at adding it to FreeSwitch, Yate, OpenSer/Kamailio, OpenSIPS and the various varients.

So, what have we done so far? well, one thing we never really had with any of the existing systems was a clear view of what’s going on “right-now” on our systems, so we said: “it would really be great if we could know how many call hits we’ve received during the past 15, 30, 45 or 60 minutes” – so here is what we made:

Inbound call statistics for 30 minutesThe above image shows our top 10 inbound DID numbers, as you can see these are in the 972 and 447 country codes (yes, we work mainly in Israel and the UK). At the backend, our servers are analyzing the data in real time, generating an active alert in the case a DID number’s statistics change in a somewhat drastic change, thus, establish a traffic anomaly. Another thing that interested us was our usage across multiple servers, which we are exhibiting in the below graph:

Traffic by server spread

Now, as you can see, the top graph shows a discrete anomaly:

Discrete traffic anomalyThis anomaly indicates something went wrong on all our servers between 00:45 and 1:15, which gives us a fairly discrete period of time to seek for a problem in the system. What happened was that one of the guys updated a portion of the data traversal API – basically deleting it 🙂 [we resumed full work after about 40 minutes].

So, where is it all going to? well simple, a new Open Source based service that we’ll be launching within a few months from now. Our intention is to provide a means for simple, straight forward, highly reliable, call analytics, fraud management and profit leakage analysis service. A service which is based upon a simple to use API on one hand and Open Source based data gathering agents. Our belief is that by analyzing large amounts of data, from multiple sources around the world, we’ll be able to ascertain the fingerprint of a telecom bound attack – being able to alert the respective users of the service and maybe in the later future, also provide a means to block the attack as it advances across the world.

I’ll be updating about our advancement as we go along, but for the time being, this is something I felt would interest you.

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