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Smartico Develops a Rockstar AI Predictive Tool for CRMs
Knowing me, knowing you … There’s nothing we can do …
Goes the famous ABBA song of the 1970s.
Ironically, this is exactly the conundrum that customer relationship management (CRM) executives face when they design and implement a marketing strategy. Especially those in the gaming and betting industry. They know who their customers are. They know their customers could punt big.
But they don’t know the most ideal time to send a simple email to their customers. Or they don’t know the best time to push a social media post.
Shortcomings of One-size-fits-all Strategy
Oftentimes, CRM executives resort to a one-size-fits-all strategy. Take the email campaign as an example. They push their mails over the night so that the job is done by the next day. That is one neat tick on the box of weekly tasks.
But does it get the job done? The job of making the customers read the mail and follow the call for action?
Well, a no has to be the answer here. Different customers have different reading habits and different routines. The mail, for example, may not reach them at the exact time when a user engages most on the internet.
How would a CRM executive know this? That’s why we are back again to the ABBA song of the seventies: Knowing me, knowing you … There’s nothing we can do.
But not quite so now. This is 2021. And there has to be a way.
Enter Smartico’s AI Model
Smartico’s new AI tool automatically customizes the communication schedule of each and every customer, based on the real-time data on the online habits of the customer.
If X is most active during the mornings for the last six months or so, and is most likely to make a bet on that time on Sunday, it is a no brainer that the CRM executive must push the mail and social media posts on Sunday mornings.
The new module of Smartico CRM does exactly this. The AI tool analyzes the real-time data on customer behavior and predicts the optimum timings for communication.
Let’s look briefly into how it is done.
How It Works
The Smartico AI model relies on machine learning. It can make accurate predictions from large data sets. It will be of great use in customer retention. The model predicts the best time of the day to send email communication to the customers.
The model uses the user data on the existing CRM. It predicts the best time for sending communications to the user. Communications can be
- Emails
- Push messages
- Short messages
- Social media posts
The next step is to define the best time. Is it mornings, evenings or later nights? Smartico’s model uses a 24-hour time frame.
The model analyzes the past activities of a customer in the CRM database to predict the best times. Customer activities can be any of the following:
- Just being online – opening mails or seeing social media posts
- Engaging with the message – reading mails, clicking links on messages or interacting with social media posts
- Doing business – making deposit, posting a bet, or signing up
This is not a plug-and-play AI model. It needs active involvement of a CRM operator for best setup. Smartico offers a smooth interface that allows the operator to set up the tool. While it could take some hours to set up the campaign initially, the tool will provide results within much more quickly once perfected.
During the setup, the operator can perform any of the following tasks:
- Finding optimum timings for communication – The tool will offer multiple optimum timings during the 24-hour period. Human intervention is required to identify the best timing among them.
- For short term campaign – The model will predict the nearest best timing for sending a communication.
- For long term campaign – The tool will offer a range of best timings over a week for scheduling a campaign.
Simplifying AI
Smartico’s team spent long hours to create a working AI model that could improve the CRM platform’s customer retention and conversion rate. The team tried and discarded several models, and tried again, found and improved the present prediction model. It has the proven capability to improve the conversion rates.
AI is going to change the way a CRM system works, especially for highly competitive segments like betting and gaming. It is here to stay. It’s like a sweeping wave. The smart way is to harness its power to improve your CRM and enhance customer retention.
The AI systems do not come often with a low entry point. It’s high-end engineering. Smartico’s AI model is perhaps the one with the lowest entry level. It simplifies the human tasks so much so that the user does not need to worry about the architecture or data processing. Just follow the interface and see the results.
Knowing all these things, this is the best you can do – for your CRM that is.
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Traffy, a performance marketing agency specializing in in-app traffic, has seen a clear shift in how iGaming campaigns scale today.
The era of “launch and forget” in iGaming is over. The market has become more competitive, and users are more demanding than ever. Scaling campaigns is no longer just about volume — success now depends on the depth of analytics, the speed of response to user behavior, and traffic quality.
Market Transformation
In the past, scaling followed a simple logic: more traffic meant more conversions. Today, that approach no longer works. Users have become more selective, and both CPA and ROI are directly tied to post-deposit behavior.
If advertisers fail to track key performance indicators within the first 72 hours — including user activity, repeat deposits, and conversion to FTD — budgets are spent without control, and scaling turns into guesswork.
New Requirements for Scaling
Scaling campaigns today requires a much more structured approach:
- Funnel analysis within the first 72 hours to quickly identify effective setups
- Traffic segmentation and strict quality control
- Continuous monitoring of user activity, repeat deposits, and FTD conversion rates
If there is no positive performance trend within the first three days, the setup is stopped immediately. This allows teams to minimize losses and reallocate budgets toward high-performing campaigns.
Common Pitfalls of Legacy Approaches
Many operators and affiliates still rely on outdated strategies that limit their ability to scale effectively:
- Focusing solely on CPA without considering unit economics and profitability
- Scaling broadly without proper traffic segmentation
- Lack of predictive analytics in the early stages of campaigns
- Underestimating traffic quality and fraud risks
These issues lead to unstable performance, rising CPI, and a loss of control over ROI.
The Traffy Approach
At Traffy, we build scalable infrastructure designed to manage in-app traffic with a performance-first mindset.
- Traffic quality control: black and white lists, ongoing audits, and integrated fraud analytics
- AI-driven optimization: algorithms that predict campaign performance and dynamically reallocate budgets toward the most efficient setups
- Performance focus: real-time analysis of the first 72 hours, deep segmentation, and continuous monitoring of key metrics and ROI
This approach allows us to scale only the traffic that is proven to be profitable, reducing risks and improving predictability at scale.
Conclusion
A performance-driven approach has become essential for scaling In-App campaigns in iGaming. The key to success lies in deep analytics, traffic segmentation, predictive modeling, and strict control within the first 72 hours.
The market has changed — and those who succeed are not the ones who scale volume, but those who scale quality traffic.
At Traffy, this approach is at the core of how we build and scale campaigns, ensuring sustainable growth and measurable performance for our partners.
The post Scaling In-App Traffic in iGaming: A Performance-Driven Approach appeared first on Eastern European Gaming | Global iGaming & Tech Intelligence Hub.
Traffy, a performance marketing agency specializing in in-app traffic, has seen a clear shift in how iGaming campaigns scale today.
The era of “launch and forget” in iGaming is over. The market has become more competitive, and users are more demanding than ever. Scaling campaigns is no longer just about volume — success now depends on the depth of analytics, the speed of response to user behavior, and traffic quality.
Market Transformation
In the past, scaling followed a simple logic: more traffic meant more conversions. Today, that approach no longer works. Users have become more selective, and both CPA and ROI are directly tied to post-deposit behavior.
If advertisers fail to track key performance indicators within the first 72 hours — including user activity, repeat deposits, and conversion to FTD — budgets are spent without control, and scaling turns into guesswork.
New Requirements for Scaling
Scaling campaigns today requires a much more structured approach:
- Funnel analysis within the first 72 hours to quickly identify effective setups
- Traffic segmentation and strict quality control
- Continuous monitoring of user activity, repeat deposits, and FTD conversion rates
If there is no positive performance trend within the first three days, the setup is stopped immediately. This allows teams to minimize losses and reallocate budgets toward high-performing campaigns.
Common Pitfalls of Legacy Approaches
Many operators and affiliates still rely on outdated strategies that limit their ability to scale effectively:
- Focusing solely on CPA without considering unit economics and profitability
- Scaling broadly without proper traffic segmentation
- Lack of predictive analytics in the early stages of campaigns
- Underestimating traffic quality and fraud risks
These issues lead to unstable performance, rising CPI, and a loss of control over ROI.
The Traffy Approach
At Traffy, we build scalable infrastructure designed to manage in-app traffic with a performance-first mindset.
- Traffic quality control: black and white lists, ongoing audits, and integrated fraud analytics
- AI-driven optimization: algorithms that predict campaign performance and dynamically reallocate budgets toward the most efficient setups
- Performance focus: real-time analysis of the first 72 hours, deep segmentation, and continuous monitoring of key metrics and ROI
This approach allows us to scale only the traffic that is proven to be profitable, reducing risks and improving predictability at scale.
Conclusion
A performance-driven approach has become essential for scaling In-App campaigns in iGaming. The key to success lies in deep analytics, traffic segmentation, predictive modeling, and strict control within the first 72 hours.
The market has changed — and those who succeed are not the ones who scale volume, but those who scale quality traffic.
At Traffy, this approach is at the core of how we build and scale campaigns, ensuring sustainable growth and measurable performance for our partners.
The post Scaling In-App Traffic in iGaming: A Performance-Driven Approach appeared first on Americas iGaming & Sports Betting News.
Traffy, a performance marketing agency specializing in in-app traffic, has seen a clear shift in how iGaming campaigns scale today.
The era of “launch and forget” in iGaming is over. The market has become more competitive, and users are more demanding than ever. Scaling campaigns is no longer just about volume — success now depends on the depth of analytics, the speed of response to user behavior, and traffic quality.
Market Transformation
In the past, scaling followed a simple logic: more traffic meant more conversions. Today, that approach no longer works. Users have become more selective, and both CPA and ROI are directly tied to post-deposit behavior.
If advertisers fail to track key performance indicators within the first 72 hours — including user activity, repeat deposits, and conversion to FTD — budgets are spent without control, and scaling turns into guesswork.
New Requirements for Scaling
Scaling campaigns today requires a much more structured approach:
- Funnel analysis within the first 72 hours to quickly identify effective setups
- Traffic segmentation and strict quality control
- Continuous monitoring of user activity, repeat deposits, and FTD conversion rates
If there is no positive performance trend within the first three days, the setup is stopped immediately. This allows teams to minimize losses and reallocate budgets toward high-performing campaigns.
Common Pitfalls of Legacy Approaches
Many operators and affiliates still rely on outdated strategies that limit their ability to scale effectively:
- Focusing solely on CPA without considering unit economics and profitability
- Scaling broadly without proper traffic segmentation
- Lack of predictive analytics in the early stages of campaigns
- Underestimating traffic quality and fraud risks
These issues lead to unstable performance, rising CPI, and a loss of control over ROI.
The Traffy Approach
At Traffy, we build scalable infrastructure designed to manage in-app traffic with a performance-first mindset.
- Traffic quality control: black and white lists, ongoing audits, and integrated fraud analytics
- AI-driven optimization: algorithms that predict campaign performance and dynamically reallocate budgets toward the most efficient setups
- Performance focus: real-time analysis of the first 72 hours, deep segmentation, and continuous monitoring of key metrics and ROI
This approach allows us to scale only the traffic that is proven to be profitable, reducing risks and improving predictability at scale.
Conclusion
A performance-driven approach has become essential for scaling In-App campaigns in iGaming. The key to success lies in deep analytics, traffic segmentation, predictive modeling, and strict control within the first 72 hours.
The market has changed — and those who succeed are not the ones who scale volume, but those who scale quality traffic.
At Traffy, this approach is at the core of how we build and scale campaigns, ensuring sustainable growth and measurable performance for our partners.
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