CPattern’s CEO, Shefer, Reveals the Theory, Practice of Retention Automation

Many brokers are facing the challenge of retaining clients in a cost-effective way. CPattern's CEO Oded Shefer talks retention automation.

Recent buzz in the industry is the amazing success of Plus500 that was known to retain clients without any call center. CPattern provides Retention automation technology and Oded Shefer, the company’s founder and CEO, gives us his angle on this very interesting field:

Can you please explain what Retention Automation is all about? 

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Absolutely. Automation is aimed to save brokers’ resources by letting machine do parts of human labor. Automation not only reduces operational costs but also increases brokerage efficiency and increases the ability to generate revenues from existing clients.

CPattern identifies three main levels of automation: traditional retention, which consists entirely of human Account Managers who work in a call center and use a CRM to document their work. In addition, there is partial automation – more specifically, this is where brokers identify costly human work aspects and find ways to automate certain processes to save time and resources.

I can name a few examples of this, such as back office automation. As no Account Manager is able to process every account activity every single moment – CPattern’s AMC (“Account Monitoring & Control system) analyzes traders’ behavior and provides alerts in real-time. This automates part of the Account Manager tasks (data collection, data analysis). It increases the capacity of the Account Manager and helps him process more information at a given time frame.

Moreover, an example of partial automation is front-end automation. For pre-defined critical scenarios, it is possible to generate electronic communication with the trader, which saves human labor (phone calls/e-mails) and expenses.

Finally, the third level we define is full automation – this is where no human labor is required at all and all retention work is done automatically. Plus500 is probably the most advanced operation which is known to do so.

Oded Shefer, Founder & CEO, CPattern
Oded Shefer, Founder & CEO, CPattern

Can you describe the effect of Retention Automation in Practice?

Today, CPattern helps brokers shift from traditional retention to partial automation with very clear ROI. The Account Monitoring & Control system (“AMC”) was launched in 2014 to help online brokers manage their accounts and increase retention performance. The AMC scans the trading activity in real-time (like a radar), to detect dozens of pre-defined scenarios. It then alerts the broker’s back office so that Account Managers are able to know the status of every account and make higher quality engagement.

Simple example – if a particular account has made a large winning trade, the AMC will enable immediate engagement with this trader to see if he is willing to consider expansion of his trading activity (e.g. account upgrade). With traditional practices, the Account Manager will make contact in a matter of hours or days which could become irrelevant for the trader and reduce the potential impact of any engagement.

A proper Retention Automation system can analyze many different types of complex events and alert on various retention scenarios. CPattern’s AMC system tracks dozens of trading and profiling variables for each trader, and alerts such scenarios as they occur.

In order for us to prove that automation has an effect, let’s look at some numbers. We selected 6 leading brokers who worked with CPattern’s AMC in April 2015 for analysis. The table below shows the average re-deposit in $ and % of depositing clients:

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ParameterAMC groupControl groupUplift
Average re-deposit ($)$831.5$367.27+126.4%
Average % accounts making a deposit23.5%17.4%+34.9%

These findings clearly show that Retention Automation can have a dramatic influence on brokers’ efficiency and as a result improve retention performance.

Is this a reliable form of benchmarking?

Retention Automation needs to be good in practice according to clear KPI’s and not only in theory. Ideally, brokers need to be able to see the effect of automation and constantly make adjustments to their work routines according to reliable numbers.

For example, CPattern uses a randomly selected Control group of accounts that would serve as a benchmark. At the end of every month, analysis is carried out to compare the trading volume in the AMC group and in the Control group (re-deposit rate and % of depositing clients). It is assumed that any difference between the AMC group and the Control group could only be attributed to the AMC as all other factors apply the same for each group.

Looking at the numbers, there seem to be a clear difference in favor of the AMC groups comparing to the control groups. In real life, I believe this is one of the most reliable ways to show an effect. However, we are always willing to consider any form of benchmarking that makes sense.

This is a very dramatic effect – how do you explain it?

Like I said, following CPattern’s alerts and engaging clients in real- time seem to increase the Account Managers’ efficiency:

  1. When the Account Manager engages clients in real-time based on significant issues – he is able to make more impact as opposed to call in a time delay.
  2. The Account Manager can handle more accounts per time unit and make better priorities
  3. Less accounts are left unattended

Is it possible to attribute the effect to large re-deposits?

Assuming standard distribution, large deposits (e.g., above $25,000 monthly) appear at the same frequency in the test group and in the control group so the effect should be statistically balanced. Exclusion of these records from both groups should result in the same ratio. 

Could it be that April was a good month for all the industry and the AMC is just “riding the trend”?

In statistics, the conservative hypothesis is that the AMC should not have any effect unless proved otherwise. If April was a good month, then there should not have been any difference between the test group and control group and both of them should have been higher than previous months. As the control group was randomly selected – the only factor differentiating between the groups was the AMC, which is assumed to be responsible for the effect. If the AMC shows MoM advantage, it could indicate that the effect is stable and not related to time of year. 

What is your message to the industry regarding automation?

Automation is very common in all industries and it is now available to the online trading industry. Even partial automation could improve brokers’ performance compared to traditional retention practices. The ability to respond in real-time to meaningful events could be critical both in saving time and in providing better care to clients. It appears that when brokers adopt a systematic approach, data driven work, and quantifiable methods – they are able to achieve a much higher performance levels. This is why we perceive ourselves not only as a B2B provider but as an important business partner to our clients.

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