Predictive Analytics Offer New Take on Direct Mail Marketing
- Commercial Real Estate
- CREtech Blog
As digital marketing has become more widespread, it has developed into an essential tool for real estate agents in every sector, including commercial real estate. Direct mail marketing remains a popular and effective marketing technique, yet it can be expensive, particularly considering the broad scatter approach involved. It is not uncommon for real estate agents to spend thousands of dollars on direct mail marketing within a single zip code with no real assurance of the return they will receive on their investment. The real problem is that agent could easily spend thousands of dollars on direct marketing to homeowners who have no interest in selling their home at all.
Enter Predictive Analytics
Analytics has become a reliable method for helping online marketers better understand the return on investment they can expect from various marketing strategies, thus driving greater results and cost effectiveness. With predictive marketing and analytics, a new breed of real estate agents are able to target homeowners who have a higher likelihood of selling their current home or even of purchasing a new home. As a result, real estate agents are able to target the greatest percent of homeowners who have the highest chances of buying or selling. Consequently, it becomes possible to save thousands of dollars on direct mail marketing campaigns.
More Companies Offering Predictive Analytics
An increasing number of companies are now providing such services, including RealAgile and SmartZip. By gathering data from a variety of sources, such companies are then able to more reliably predict which homeowners are more likely to buy and sell. A variety of factors gathered from data, both private and public, are used for making such determinations, including occupation, marital status, income, and age. When combined, such cumulative data helps marketers to gain a truer sense of the bigger picture, thus making it possible to predict prospective buyers and sellers with greater accuracy.
An example would be a couple who recently had a child. There is a greater probability that such a family would be interested in buying a larger home. While this might not be the case with all such families, it does provide the basis for how predictive analytics works. SmartZip is currently one of the most well known such real estate analytics firms in the industry and uses hundreds of different models to compare thousands of variables in order to identify the best model to use for each market. RealAgile works in a similar manner by utilizing vast amounts of data in order to construct predictive models that will predict the chances that a homeowner may be ready to sell their home and purchase another home. The firm also calculates a MoveScore for properties in specified territories.
As digital marketing becomes more complex, real estate agents in all sectors must learn to leverage technology in order to up their marketing gaming. Predictive analytics makes it possible to rely on the tried and true method of direct marketing while working to increase return on investment and lower overall advertising costs.
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