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Technology platform to predict breakout companies in the DTC market

Technology platform to predict breakout companies in the DTC market

Combining the power of multiple non-traditional data sources we are building the first European platform generating actionable leads and help agents gain first-mover advantage.
Real estate Leader

Real estate Leader


“I looked for a lot of agencies in the market as there are huge technical challenges to overcome in my project. I chose Ludotech an agency with broad experience in data but above all a product-oriented team. ”

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The Need

Over the past few years, many real estate firms have made decisions based on intuition, traditional data collection, analysis, and conventional prospecting methods. On prospecting alone, keeping track of clean data is tedious. Sifting through millions of records and analyzing them to identify clear patterns to generate a list of prospects is a nightmare. This conventional method slows down the decision-making process hence slowing down the entire sales cycle. By the time the relevant data have been collected, filtered, and processed, the best opportunities are gone. In other words, being slow to identify the best leads, whether on properties or prospective clients, means being behind on the tough real estate race.Traditionally, real estate firms would look into massive amounts of data to find trends, identify where to acquire property or their following big projects, assess conditions, and see where to build or divest. Real estate agents or brokers, on the other hand, would also use multiple sources to obtain information on which valuable property would be up for sale in the coming years and see who are the prospects to tap into to close a deal. With data becoming more challenging to tame, the frustration grows from the time it takes to gather, analyze and harness needed information for actionable insights. And with only a few supporting tools to aid in obtaining the correct information that triggers the subsequent right actions, real estate agents, brokers, and investors are left with the inefficient tasks of manual data gathering and analysis.Without an advanced analytics tool to optimize the entire sales cycle, these time-consuming manual tasks take away a considerable chunk of time from what matters the most - closing the sale.


The Challenge

Initially, to produce a list of prospects, the client and his team used Microsoft Excel as the primary tool to manually enter and analyze data from multiple sources. Using this database, the client then applies a proprietary model obtained through his 20 years of experience. Simply adding, editing, and looking for specific information gets more complex as new data gets added. We see countless issues using Excel for an industry that uses billions of data points; Issues include consolidation, data maintainability and scalability, inability to support collaborative work, failure to support quick decision-making, and extreme susceptibility to human errors.As numerous people use this same database simultaneously, data consistency and reliability became an issue. A spreadsheet will contain one error for every 20 cells with data, on average. The team kept modifying the database without noticing errors or corruption, resulting in inaccurate data and skewed decision-making. Now, regarding data quality and availability. Sifting through millions of gathered data for analysis is already a significant hurdle. Filtering was a big issue as harnessing specific information when required couldn't be done quickly. And were they looking at the best sources? Without an application powered by advanced analytics to leverage open data, a rich plethora of public information such as records of property owners and locations, historical transactions, building permits, price trends, registry of local businesses, to name a few, remain largely untapped.The conventional gathering, storing, analysis without effective data filtering held the business back from innovation. The client was serious about profit growth and has sought Ludo to unlock new opportunities, open new possibilities, and ultimately, get an edge over the competition.


The Solution

The core idea is to disrupt the entire prospection process - to help the client do efficient prospection work and reduce costs. This means finding prospects fast - those that are most likely to be sold to or properties that are more likely to be put up in the market soon.To do this, we created an advanced analytics application that was combined with an extensive database of traditional and nontraditional data to predict property valuation, properties that will be up for rent or sale in the coming months, and a list of candidates to reach out to for the next sales phase. Technology solutions were implemented that automate continuous data collection and ingestion from multiple sources like public APIs or web data scrapping at large.Many of the data sources were populated by local government agencies in which human interactions can introduce tons of errors, including typos like incorrect letters, numbers, and entry duplications. After fetching the raw data, various data cleansing and normalization methods were applied to ensure that it conforms with validity, accuracy, completeness, and consistency. The cleaned data were then integrated into a new platform powered by a dedicated database to support collaborative work and ensure that data quality couldn't be altered despite being used simultaneously by multiple users.Make better decisions powered by machine-learning algorithms. The application continuously collects and ingests data on a large scale. By deploying machine-learning algorithms, the longer the software is used, the more extensive information it holds, and the more intelligent the algorithm becomes. In other words, over time it can provide a more accurate list of prospects and better suggestions on the next best decisions to take. The suggestions can include: whom to prioritize in a particular city, who are the best candidates to add to a campaign, or which prospects to reach out to at a specific time. It's simple - targeting pre-qualified leads can maximize the effects of any campaign, leading to a massive reduction in operational costs and the biggest chance of closing the sales. After all, it's not raw data that creates value, but the ability to extract patterns and use those predictions to supply more accurate recommendations.


The Result

By using the power of advanced analytics, automated data collection from multiple sources at a large scale became a lot easier. Creating a more personalized engagement to targeted leads can be made automatic. Data corruption and fraud due to human error were eradicated, and collaborative work done anywhere and at any time was made possible through using AWS. By deploying machine-learning algorithms, the tool will continuously extract patterns and provide more powerful insights for better decision making, and overall, provide a better list of leads over time. All the client has to do is polish his offers and scripts, and then initiate the first contact.In summary, traditional prospecting methods are time-consuming, which translates to slow sales. By the time the relevant data have been collected, filtered, and processed, the best opportunities are gone. Using an advanced real estate analytics tool that uses machine learning algorithms, you can generate a rich list of prospects fast. Whether you're a real estate developer, asset manager, or broker, an advanced analytics tool can collect, manage, extract patterns and interpret data for actionable insights. In other words, you can shorten the sales cycle by more than half the time it typically takes and focus your time and energy on what matters most - closing the sale.
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