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Leveraging Data Analytics: Benefits and Use Case Examples for Property Agents

October 2, 2023
MALAYSIA

Property agents operate in a dynamic and fiercely competitive market, where they encounter multifaceted challenges in identifying potential sellers and buyers, comprehending market trends, and making well-informed decisions amid challenging and uncertain market conditions.

Amidst these challenges, data analytics has emerged as a game-changer, revolutionising the way property agents conduct business. By harnessing the power of data analytics, real estate agents and negotiators are bestowed with actionable insights and data-backed decision-making tools that empower them to thrive and deliver exceptional service to their esteemed clients.

The benefits of leveraging data analytics for realtors is discussed below along with sample use cases:

Improved Decision-Making

Data analytics tools like DataSense equip property agents with a wealth of information, enabling them to make informed decisions based on market data. By leveraging analytics tools, agents can identify emerging trends, understand price dynamics, and predict future market conditions.

This information empowers agents to recommend optimal pricing strategies, determine the right time to buy or sell, and advise clients on investment opportunities. With access to accurate and latest available data, agents can confidently guide their clients through the complexities of the real estate market.

Use Case: John has a client looking for an investment property. By looking through past transactions he narrows the search for properties and identifies a few serviced apartments units that are selling below market value with a decent rental yield. By using data-backed sources, he is able to prepare a more convincing proposal for his clients and aid them in making a more informed decision.

Enhanced Market Insights

One of the significant advantages of data analytics is its ability to provide property agents with valuable market insights. Analytics tools can interpret vast amounts of data, including property sales history, demographics, market demand, and economic indicators. By analysing this data, agents can identify target markets, understand buyer preferences, and tailor their efforts accordingly.

For instance, they can identify neighborhoods experiencing rapid growth, pinpoint desirable property features, and create effective marketing campaigns that resonate with potential buyers. Armed with these insights, property agents can position themselves for a better chance at success as well as avoid wasting time, effort and money on unfavourable properties.

Use Case: Farah is a subsale real estate negotiator looking for a new coverage area to focus her efforts. She identifies a few upcoming townships in Shah Alam. She studies past transactions and notices some of these townships and neighbourhood are lacking in subsale transactions and prices have trended downwards since launch. Homeowners are less likely to sell their property at a considerable loss so this reduces the potential units she can add to her inventory. She then identifies a township with frequent transactions for landed terrace homes and demonstrated steady price appreciation, so she targets homeowners in the area and significantly increases her chances of securing sellers and buyers.

Realistic Prices

Among the most significant challenges property agents face is the issue of pricing, as it involves dealing with conflicting interests and ambiguity. It is in the interest of sellers to get the highest price possible while buyers aspire for a good deal.

Only registered valuers are allowed to provide a valuation and they do have an invaluable tool at their disposal. ProxyPrice allows valuers to receive property price valuation estimate data quickly on the value of the target property with reliable and up-to-date sources.

However, in practice, it can often be a challenge to convince ignorant homeowners to pay for a valuation. More often than not, valuation is done by a bank’s appointed values after a buyer is secured. Hence, property agents often find themselves needing to advise clients on the potential market value and advertise at more realistic prices to invite enquiries on property portals. This is where property agents can rely past transaction data of specific properties or neighbourhoods via PropertyGuru DataSense. Historical transaction data offers proof to homeowners how much similar properties have sold for and is more realistic than market data from property listings which fluctuate, sometimes overpriced or contain duplicate units.

Sample Use Case: Jack meets a homeowner who wants to sell off his condo unit urgently. He compares current listings on marketplaces and finds very few listings, some of which are overpriced. He researches past transactions within the building and proposes a more realistic market value to advertise the unit. Because Jack is advertising at the right price, he is able to effectively sell the unit for the owner.

Targeted Marketing Strategies

Data analytics enables property agents to create targeted marketing strategies that maximize the visibility of properties in the market. By analysing data on buyer preferences, demographics, and online behaviour, agents can identify the most suitable channels to reach potential buyers.

Whether it's through social media platforms, online listings, or targeted advertising campaigns, agents can optimize their marketing efforts to ensure their listings reach the right audience. This targeted approach saves time and resources, increasing the likelihood of attracting qualified leads and closing deals faster.

Use case: Kate is a real estate negotiator focusing on project sales. She uses PropertyGuru DataSense to research into similar nearby buildings around her current project. She finds the demographics of these owners to largely be younger Malay homeowners predominantly within the age range of 30 – 40 years old. She then plans and refines her ad campaigns on platforms such as Facebook and Google to target this demographic.

Key takeaway

The benefits of data analytics for property agents are undeniable. By leveraging the power of data, agents can make informed decisions, gain valuable market insights, accurately value properties, implement targeted marketing strategies, and deliver exceptional client service.

In an industry where knowledge and agility are paramount, data analytics equips property agents with the tools they need to succeed in a highly competitive market. As the real estate landscape continues to evolve, property agents who embrace data analytics will have a distinct advantage, setting them apart as industry leaders.

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