In real estate, the adage “garbage in, garbage out” rings disturbingly true. Inaccurate MLS data undermines the system’s utility for buyers and sellers. With over 90% of home searches starting online, poor data quality frustrates consumers and strains agent relationships.
For buyers, inaccurate or incomplete listings lead to the inability to effectively filter properties online. Hours spent touring unsuitable homes waste time. Contradictory listing details between sources causes confusion and delays. Opaque listings result in more physical visits to compensate for unknowns, increasing hassle. Waiting on answers to basic listing questions breeds dissatisfaction. Bad data essentially sabotages an efficient, informed search.
The downstream effect of bad data falls heavily on agents. Inaccuracies multiply inquiries as buyers try to fill gaps through their agent contact. These bloats call volume and emails. As subject matter experts, agents get pressed into verifying details that should be confirmed before listing input. Constant correction and clarification disrupt deal progress. The workload escalates for individuals confronted with fixing systemic data issues.
Lower listing performance
Listings with inaccurate facts, questionable claims, or sparse details discourage interest. Buyers’ real estate MLS questioning simple attributes like bedroom count lose trust. Photographically undersold homes languish as buyers skip viewings. Vague listings generate fewer showings. And properties that sit may end up underpriced for a hasty sale. Poor quality listings undermine maximum value. In addition to dissatisfied clients, incorrect data heightens legal risks. Inaccurate square footage claims can facilitate lawsuits, especially if large discrepancies. Overstating property attributes like remodel year or appliance replacements border on misrepresentation. Even typos like wrong school district or tax amounts can complicate transactions, not to mention violate MLS rules. Data integrity problems open Pandora’s Box of liability.
Shoddy listings also hurt agent and brokerage reputations. Buyers may wrongly assume the agent is at fault for any listing inaccuracies, unaware that agents merely input seller-provided data. They are allowing subpar listings into the MLS signals tolerance of low standards. And dissatisfied buyers impacted by inaccurate data may generalize feelings about that listing to impressions of the firm. Data issues undeservedly harm reputations.
Strategies for improvement
MLS platforms granting consumers online access place responsibility on brokers to champion listing data quality. Tactics include:
- Implementing required listing input fields and drop-down selections with the MLS vendor to enforce completeness.
- Establishing brokerage data accuracy guidelines and QA protocols for confirming details.
- Offering regular training to agents on listing verification best practices.
- Incorporating listing quality into agent evaluations and recognition programs.
- Auditing listings regularly as part of risk management.
- Soliciting client feedback on their search experience to pinpoint data problem areas.
- Advocating that MLS committees implement data standards and audits across all participants.
Clean, reliable listing data benefits everyone involved. While chasing perfection may prove elusive, making meaningful strides to improve MLS information quality removes unnecessary frustrations from an already stressful transaction.