Why Builders and Realtors Need to Analyze Big Data

Big data has suddenly become big business. If you are a builder or a realtor, how can you benefit by gathering and analyzing big data? Will data help you sell more homes?

Yes. You might assume that only big organizations need to harness the power of big data. Far from it. Both small and large real estate companies can run their businesses better by analyzing customer data. However, a good understanding of how big data helps your business is essential to develop a suitable business strategy.

Data becomes valuable only when you analyze it. And proper data analysis helps you know your customer better.

Data analysis helps you gain an edge over your competitor

Several builders and agents still don't take the time or trouble to gather data about their target customers. By simply gathering and analyzing data, you can gain an edge over your competition.

By analyzing data, a real estate company can find out what kind of homes sell well in a particular locality. This knowledge will help the builder launch the right project in the right locality.

Data also helps builders and realtors find people who are more likely to buy or sell homes in the immediate future. This will help them create a marketing strategy that targets the right group of buyers.

Data gives you more comprehensive demographic information. It also shows you why certain category of homes sells well in certain localities.

Launch better marketing strategies

After analyzing big data about your customers and the real estate industry, you can use that information to expand your business. One advantage of using big data is that it helps you improve your marketing strategies.

If you run a website, by simply looking at who is visiting your site, you can create a marketing strategy tailor-made for them.

When you have access to data which shows you who your target customer is, you will have no difficulty launching a more personalized marketing strategy.

This kind of analytics is useful for several types of businesses. Data also helps you adapt your marketing strategies for future buyers.

Data helps you decide whether you should implement a marketing strategy or not

By simply analyzing the data gathered by your analytics software, you can decide whether or not you should implement a new marketing strategy. If you market your homes or services to people who are not interested in being a buyer or seller anytime soon, you are simply wasting your time and resources.

When you have real data about your customers and the real estate industry, you can find out whether you should expand your business to other markets.

Realtors sometimes make business decisions with no reason. However, when you work with data analytics, you can make sound business decisions with a reason. A well-thought out business strategy will only benefit you and your company.

How to gather data

It is not difficult for a real estate company to gather data. Most of them already run websites. By simply analyzing the key phrases that attract people to their website, a builder can find valuable information about their potential clients. Both free and paid data analytics software solutions are available.

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How Small and Medium Sized Real Estate Companies Can Benefit from Data Analytics

Data is being generated at an alarming pace. Every action that we perform today helps create data. Needless to say, in today's business world, data is a big force to reckon with.

Thanks to the availability of computers with large memory and storage, storing vast amounts of data is no longer a big deal. And hence small real estate companies have no excuses for ignoring the need to gather, store and manage data that pertains to their business. In fact, by using data analytics, a small builder or a realtor can gain advantage over their competition.

Here is why you need a data analytics strategy to retain your competitive advantage:

It helps you create a personalized experience for your customers

Customers are getting more and more demanding. These days, all customers want an experience which is tailor-made for them. Gone are the days when one size would fit all. But that is not surprising. Since you are working with customers of all kinds, it is not easy to create one business model or user experience that fits everyone.

On the flip side, if you have collected massive amounts of data, you can create an experience that will satisfy an entire category of customers having similar interests or needs. If you don't know anything about your customers this simply isn't possible.

Data analytics make your marketing more effective

Your marketing strategy should be designed to target specific groups of customers. If your marketing messages are personalized, the customer will get the impression that they are dealing with a trusted friend or associate. In other words, by leveraging data, you can create that personal connection with the customer.

By collecting as much information as possible about your customers, you will get to know them better. This will allow you to create personalized messages.

Data helps you clear your wrong assumptions

Many small real estate companies don't know what their customers want. They simply assume that they know everything but they don't.

By collecting and analyzing data about how you run your business, you can save yourself many troubles. If, on the other hand, your business strategy is built upon wrong assumptions, you will lose lots of money. Data analytics help prevent these problems.

It helps you identify your target markets

Who is your customer? Who are the people who buy your homes or hire your service? Until you know the answers to that question, you are simply guessing things. When you know who your customers are and what they want, you will be able to create an appropriate marketing strategy. This will also help you branch out into other markets.

Data analytics and quantification are great tools for your business. By making a small investment today, you can reap huge benefits later.

The resources that a small real estate company needs to implement data analytics are: data, the right tools and expertise. Data is now readily available. Thanks to open source technology, data analytics tools are also available. The only missing element is the expertise to analyze data.

However, if you are using a pre-packaged basic model, the expert support is needed only once.

By spending a few hundred dollars a month, a small business can host and maintain its data analytics model on a cloud-based server. The investment will result in productivity enhancements and typically pay for itself in a few months.

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The Growing Importance of Data Analytics

It seems that retail is fast emerging as the biggest adopter of big data. Nearly every global retailer is exploring how big data analytics can help to decode consumer behaviors and penetrate segments that have traditionally remained outside their reach. However, this doesn’t mean that other sectors aren’t sensitized towards the growing importance of big data.

Retail Might be Leading but Real Estate is Driving the Big Data Wave Too

Healthcare is aggressively pursuing the path of digitization and big data plays an important role in this journey. Real estate institutions are increasingly acknowledging big data capabilities which give them a better chance to evaluate risk and add more value to customer services. Real estate firms are using big data to re-assess traditionally unserved consumer demographics and create more sustainable customer relationships.

Real estate has always been among the biggest creators of consumer data. Somehow, this fact wasn’t widely acknowledged until recently. Even when retailer activities were limited to merely creating summarized bills, real estate was creating lots of useful consumer data. This included details about household incomes, bill payment patterns, and credit history.

Data Analysis Driving Real Estate Decisions

Today, realtors understand that their consumer facing activities need to imitate the big data efficiencies that retailers have gained. This means capturing, storing, cleansing, indexing, and analyzing data for better outcomes. The role of traditional data centers has changed. Earlier, consumer interaction wasn’t as conclusive. Now, consumers review, recommend, and emote about nearly every product/service. This includes conversations about brand loyalty or buying preferences. These conversations provide valuable insight into how geographical and regional demographics affect property buying or refinancing decisions.

Contemporary data centers need to be more proactive to consistently stream the web for such meaningful data. From time spent per webpage to the number of clicks per banner ad, and daily webpage views, most types of browsing patterns can be quantified. Once expressed numerically, they can be further analyzed. The analysis yields actionable information—this kind of data helps managers to take decisions with more confidence.

Using big data analytics, real estate businesses can optimize their products, services, and even webpage layouts and promotional messages. The idea is to be in sync with the mindset of consumers. Some other benefits of an effective data analysis team include:

• Ease of conducting market segmentation studies
• Identification of points of losing consumer interest
• Evaluation of efficiency of different points of sale
• Evaluation of consumer engagement efficiency across different channels like physical campaigns, calls, emails, and mobile offers etc.
• Gaining future readiness, i.e. being intuitive about emerging market trends
• Gaining insight about internal processes and staff performance
• Developing better, more sensitive competitor pricing strategies
• Local and regional market analysis for revenue growth forecasts
• Establishing seasonal patterns in revenue hikes or dips
• Ease of conducting consumer sentiment studies
• Real time monitoring of established and emerging consumer behaviors

Please understand that big data becomes fully useful when a business can gain multi-channel analysis and large scale improvement capabilities. A true big data infrastructure should drive improvement of internal processes like supply chain, recruitment, and even administration. Every internal dynamic of a business, ranging from logistics to warehouse optimization, can be enhanced with big data analysis.

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How Experimentation Can Fast Track Big Data Capability

As more businesses explore the vast expanse of big data utilities, it is becoming clear that big data delivers more when managers are ready to be a bit creative. For a real estate business, big data can provide many standard utilities. Standard because soon most of the real estate organizations will gain similar big data advantages—this trend is already underway. So how does a real estate business make itself unique and more competitive?

This is where experimentation comes to the fore. Big data analysis can yield lots of actionable information provided you are ready to take some chances, allow room for creative experimentation, and use data sources that seem irrelevant at first sight. Here we discuss more about how experimentation can drive better ROI for your big data investment.

Big Data is Being Widely Embraced, but Who Will Benefit More?

We understand that big data is still new for most organizations. They are approaching big data with some apprehension along with lots of enthusiasm. It is unfair to expect such businesses to get creative with big data at the outset. This doesn’t make sense, particularly when digitization hasn’t been associated with the real estate industry in a larger perspective. We realize that most businesses in this niche are finding it difficult to let go of their legacy protocols, wanting to hold on to the traditional methods of working. However, the big data voyage has begun, and soon most businesses will be at ease working in a data-driven environment.

There is another aspect to this realization—some organizations have adaptability as a part of their core skills. On the contrary, some are deep rooted in hierarchies and don’t venture beyond the realm of expected outcomes. It seems that the more adaptable businesses have a better chance of extracting better ROI from their big data adoption. The more established businesses will take time as their bigger teams and numerous offices multiply the hierarchy, breeding lesser elasticity.

Big Data can Look Ungainly, But Don’t Fret - Placate Your Team

Big data involves high volumes, mammoth disparities, and real time performance. This means lots of data is collated from various resources, including data that is highly unstructured and processed in real time. During the initial few weeks, you might feel that your big data team is trying to do too much. However, don’t have doubts about this—the typical big data environment is very challenging and to others, it can seem very perplexing.

Data analysts work together, forming strategies on the go, hungry for processing more data. Once you have established a basic level of understanding with your big data team, try to establish an experimentation policy. The idea is to make the team feel that you support a certain degree of experimentation. The team should know that running correlations or comparisons that don’t amount to any conclusive information will not be ridiculed. You can ask the team to allocate certain hours or weekdays for running experimental data studies. This is vital to discover unexplored market service combinations and unearth new consumer zones.

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Big Data & Hadoop: What’s Cooking?

If you have been following big data, it is most likely you have come across repeated mention of Hadoop. Before we delve deeper into this discussion, let us take a step back in history and understand how data management has evolved and what led to the current scenario where Hadoop and big data are the favored technologies.

Understand Hadoop: The Early Days

Earlier, computing was limited in volumes and in terms of expectations from outcomes. Applications were created specifically for different data structures to ensure that a problem was comprehensively solved. Since computing volumes were humble, this approach didn’t present too many problems. Multiple data resources were uncommon, almost unheard of during this period. Using organizational databases or network data, larger applications functioned rather well. However, the relationship between data structure and application saw a major upheaval with the creation of relational databases.

Due to this, data access to SQL was standardized. More businesses started using spreadsheets. Together, these two developments created the way for more complex data management systems to emerge.

During the 90s, it became clear that there was more business value in combining data from different applications but this was challenging. Slowly, better and bigger data structures surfaced. However, this picture was soon challenged with the arrival of data-intensive business mammoths in the form of Yahoo and Google. Things changed and data didn’t have a similar, streamlined structure. These organizations were handling massive amounts of data on a daily basis, hoping to create a solution for faster access to retrieve and save data. This paved the way for the creation of Hadoop—a more dexterous, organized, and distributed file system that makes it easy to handle unstructured data.

As Hadoop Progressed, Big Data Arrived

Slowly, the advantages of Hadoop became known to businesses across the world. Managers realized that they could benefit a lot in terms of condensing their operational cycles if data access was made easier without compromising its security. The basics of free data management framework that Hadoop had initiated were then routed towards data-driven businesses that wanted data capabilities of bigger organizations.

The Hadoop-Big Data Connection—Hadoop is the platform that makes it easier for unstructured data to be fed into the big data ecosystem. Conventionally, real estate businesses were somewhat selective about retaining data. They feared massive amounts of data will not be accessible. Big data makes it easier to store everything that seems important. With big data, businesses can feel assured that their organizational and consumer data is secured and easily shareable when needed. With big data analysis, the information can be extracted in an orderly, indexed format and then assessed.

Did Google create Hadoop?

Yes, Google can be credited for bringing Hadoop to the world of IT. This happened with Google’s requirement to index enormous amounts of web data, collating, and categorizing it for its search results. Since the market at that time didn’t have a readymade platform that Google could use, it had to innovate. The platform was first called Nutch. Yahoo played a more integral role in helping Hadoop evolve for enterprise applications.

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Big Data Strategies in Real Estate

Predictive analysis and data mining are yet to become a big deal in real estate, but big data is slowly and surely penetrating this segment. Some analysts might question the relevancy of big data in a business where the consumer/homebuyer typically ventures into the market every 5 to 10 years. We argue that this is precisely the reason big data should be used in the real estate niche.

Why Remaining Connected with Customers is Necessary?

Property purchase decisions are heavily impacted by the goodwill a business can generate and sustain. Here, consumer preferences don’t undergo overnight changes like those seen among fast-moving consumer goods. Real estate industry has a special space for references where past clients are invaluable. Having happy, if not loyal, clients can translate into feeding other lines of business like refinancing. If you can maintain a connection with your past clients, many more serious queries are likely to flow from friends, family members, office colleagues, and even neighbors.

Some folks argue that typical retail businesses, like apparel, have more to benefit from big data rather than real estate. Let us take an example to argue our point here—a young family of four with working parents is expecting another child. Such information is often announced in the form of social media updates. A retail business can use this data to send emailers and SMS with links to newborn clothing range. Now, how can a real estate business use similar data?

When a baby is on the way, it is most likely that the mother has taken temporary leave of absence. There is going to be lesser money to pay the bills. With the newborn retail niche overburdened with branded products, the expenses are also likely to rise. Limited to a single income and facing more expenditure, the family might seriously consider refinancing to save money. With three children, they might reconsider moving to a bigger property.

A real estate business can make relevant interaction by emailing pictures of bigger accommodations with more study rooms and better schools. This strategy is a combination of tracking social media conversations and hyper-targeted marketing. Here, a single Facebook update can lay the basis for a new sale or at least create a very serious home-buying or refinancing query.

There is more to tracking consumers’ social media behavior. Online experts now offer targeted social media analysis. They identify audiences whose recent shopping behavior suggests a definite buying capacity. Home purchases might be offline, but online consumer behaviors can help real estate businesses identify more, promising consumers.

Big Data Strategies Deliver but Be Patient

The strategies we discussed above take time. Signing up with a social data analysis firm doesn’t mean that you will be overwhelmed with a glut of serious queries. This is a gradual process where hurrying into decisions can mean disaster. Secondly, keeping past customers engaged isn’t easy. This is particularly true for real estate where the consumer-connect is soon lost after the transaction. This is where data-sharing practices can solve the problem.

If you are ready to share data about the payment pattern or the mortgaging history of past clients, you can get valuable information in return. For instance, some of your past customers might be avid environmental enthusiasts. You can start a small blog or a newsletter about green building practices. Here, you reason to seek an association is logical since you are in the housing niche. Among consumers, such information is less likely to be spammed because it is relevant to them. The e-mailer/newsletter can carry a small, hyperlinked logo, directing the browser to your parent website.

Buy and work leads smarter, contact only the customers you want to engage, and enable your employees to be productive. Connect with your target audience with Live Connect today!