The Bottom Line on MLS Data Standards
In a post last week, I asked a pretty open-ended question: “Are the costs of an MLS [coverting to a standard format] worth the long-term benefits?” I asked this question because we have several MLSs contemplating this very question now, and I thought it might be interesting for them to hear some outside perspectives. We received some great comments on that post, and in this post I want to put some more meat on the bone by outlining in more detail the potential cost savings for regionalizing MLS data.
Importantly, there are several ways to regionalize MLS data and so I think the first requirement is defining the objectives (benefits) of regionalizing. Once the benefits are quantified, then the costs of the potential solutions can better be judged and the “bottom line” or ROI of the entire effort will hopefully be clearer.
Benefits of Regionalizing MLS Data
Some of the oft-sited reasons for regionalization are:
- Eliminate or reduce duplicate listing entry, which often means learning and complying with different rules for listing entry;
- Eliminate or reduce the payment of fees to belong to more than one MLS;
- Eliminate or reduce the costs associated with managing disparate IDX feeds and IDX rules; and
- Increase the exposure of listings to more MLS members.
The next step is to quantify these costs or opportunities.
|Cost of Duplicate Listing Entry|
|Formula||# Duplicate Listings Per Year x Cost Per Listing|
|#Duplicate Listings||Finding the number of duplicate listings is not always easy. One of the biggest challenges is that the data likely is not stored the same way for each of the MLSs involved, and so comparing addresses or parcel numbers may not be accurate. Also, you may not have ready access to the listing data from all of the other MLSs involved.Importantly, though, we’re not looking for perfection here but an estimate. In that regard, if you don’t have access to all the data for such an analysis or the address matching is too unreliable, an alternative approach would be to survey your brokerages/offices to ask them how many MLSs to which they belong and to estimate the percentage of their listings they enter into other MLSs. (This same info will be helpful in assessing duplicate membership fees discussed below.)For example, let’s say your MLS has 200 offices and ten percent (20 of them) belong to more than your MLS and have a policy of entering all their listings into those MLSs. Of those twenty, perhaps your survey finds that twelve offices enter listings into three additional MLSs, four of the offices enter into two additional MLSs, and four others enter their listings into just one additional MLS. You could then take the annual new listing count for each of those 20 offices and multiply it by the number of additional MLSs revealed from the survey for that office and you’d have a rough estimate of the number of duplicate entries for a year.|
|Cost Per Listing||There are a couple of methods for estimating the cost for entering a duplicate listing. First, you could use the cost for data entry personnel and an average amount of time for entering a listing as an estimate of the cost. For example, an average data entry salary is approximately $30,000 per year or about $15 per hour (rounding up). Assuming someone can enter a listing and upload the photos in 30 minutes on average (our time estimates are less than this, but 30 minutes is a conservative high-side estimate), the cost per duplicate listing is $7.50. On the other hand, many agents enter their own listings and so the cost really is the opportunity cost to them of their time, which is much more difficult to assess. For this reason, I’d recommend using the outsourcing cost as an estimate. However, I’d also add some additional cost for review by the listing agent and other compliance issues that arise. Accordingly, perhaps doubling the cost of listing entry is a good estimate for the cost of entering a duplicate listing. (Note: Of course, these costs may differ for you locally depending on relative salary costs in your area and other compliance requirements.)|
|Example||1,000 duplicate listings entered per year x $15 per listing = $15,000 potential cost savings per year
Caveat: I’m just making up these examples. You need to put in your own numbers for your MLS.
|Duplicate Membership Fees|
|Formula||# Duplicate MLS Memberships x Average Cost Per Membership|
|# Duplicate MLS Memberships||If each MLS uses the NRDS ID as a tracking identifier for members, finding duplicates should be relatively straight-forward if you have access to the data. Other possible matching methods are email address or, as a last resort, name and possibly street address. Or, as mentioned above, you can get an estimate of the number of extra MLSs to which members belong by surveying your membership. Again, a solid estimate is what we’re after.
In designing your survey, you should be clear that you’re asking about MLS memberships other than yours. Or, alternatively, ask for total MLS memberships and then be sure to subtract one when doing your calculations.
Another complicating matter here is that members may belong to multiple MLSs for a variety of reasons unrelated to data sharing or regionalization. For example, lock box access often is an issue that needs to be solve simultaneously with MLS data exchange. Overall, however, estimating the total number of duplicate members will provide an outside estimate of the potential cost savings.
|Cost Per Membership||The cost per membership likely will need to be an average as calculating the exact number for each person would likely be impractical.|
|Example||50 duplicate memberships x $240 average cost per membership per year = $12,000 potential savings per year.
Note: An interesting side note here is that the saved duplicate membership fees are lost revenue to the other MLSs in the region. The members save by not having to pay duplicate fees but the MLSs actually lose some revenue.
|Costs of Maintaining Disparate IDX and Other Data Feeds|
|Formula||(Total # of Data Feeds Delivered by All MLSs in Region – # of different entities receiving the feeds) x Average Cost to Maintain Each Feed
(Total # of New Feeds Delivered by All MLSs in Region – # of different entities receiving the feeds) x Average Cost to Setup Each Feed
|Total # of Feeds Delivered||This number should be relatively easy to obtain by looking at the RETS manager in your MLS system or inquiring with each MLS vendor involved.The number of new feeds delivered each year could be estimated by looking at the number of new requests received in the last year, and using that as a proxy or estimate for the number expected in the future.|
|# of Different Entities Receiving Feeds||You need to subtract the number of developers receiving feeds from the total number of feeds, because each developer would have to convert and maintain at least one feed no matter what. Note: Subtracting this number will only provide an average, because some developers may receive more than one feed from the same MLS, but, as mentioned above, we’re estimating here and this should provide a close proxy for the total extra feeds.|
|Cost of Converting and Maintaining Disparate Feeds||As an MLS vendor, we’re not on the receiving side of too many IDX data feeds, but we do have quite a bit of experience with data conversions. In a typical conversion, you have both programming and QA personnel involved and these processes collectively may take approximately 24 hours per property type to convert and test. Assuming an IDX feed would take about a third as much time (or 8 hours) and that an average MLS has 5 property types, that would be 40 hours per feed to get it set up. Assuming an average cost of $133 per hour for programming and QA, the cost to set up an IDX feed is about $5,320. (If there is anyone reading who has more exact cost estimates for converting IDX feeds than this, please comment or send me an email.)Of course, the conversion expense is a one-time cost, and, for those vendors already operating in your markets, the cost has already been incurred, and so will not be saved except for new feeds. The only cost that will be on-going is the cost to maintain the disparate feeds. Once the conversion program is written, the cost of maintenance is relatively minimal unless the MLS changes fields frequently, which is unusual. I would think a conservative (high) estimate of the cost to maintain a feed per year would be about $1,000 (7.5 hours per year at $133 per hour average for development and QA).|
|Discount Rate||A potentially important issue here is that the costs for processing the feeds often are not born directly by brokers or agents but rather by IDX and other product vendors. Accordingly, even if the process is made more efficient for these vendors, that doesn’t mean the prices paid by the brokers and agents will be lower. Of course, some brokers and franchises also hire developers in-house to process these feeds and competition likely will force prices lower over time, but it may be prudent to build in a “discount” rate on this potential cost savings to reflect that the savings may not all pass through to your members.|
|Example||(50 new feeds per year – 20 different entities receiving the feeds) x $5,320 per feed = $159,600 per year
(200 totals feeds – 50 different brokers receiving the feeds) x $1,000 per year per feed for mainteance = $150,000 per year
As mentioned above, some discount rate likely should be applied to these formulas, because all the cost savings may not be passed through to your members.
|Increase Exposure of Listings; Potentially More Sales|
|Formula||Even though this is one of the biggest potential benefits, I’m not sure it can be estimated properly. First, there is at least some argument that no increase in sales will occur because the listings that benefit from exposure in more than one MLS already are being exposed by the duplicate entry. Second, if there are some people who aren’t willing to spend the time or money on duplicate entry now such that there would be some additional or faster sales from more exposure, estimating that number would be pretty hard. Perhaps one method would be to try to find out how many inter-MLS sales there are now on the duplicate entries and extrapolate that number to the non-duplicate listing base. However, such an extrapolation is filled with potential inaccuracy given that the agents and brokers likely weren’t entering it into the other MLSs already because they didn’t see a big benefit to doing so. Overall, I think this is the area where many regionalization decisions can go awry. The potential benefit of the extra exposure and sales seems limitless and so justifies nearly any cost when, in fact, the benefit may be negligible at best.|
The above are some of the key cost savings and efficiencies that can be gained by regionalizing or standardizing the data processing for an MLS. Perhaps there are others I’ve missed or different ways to estimate the savings. Please let me know in the comments. Also, if you have numbers for your area you’d like to share as real-world examples instead of my made up examples, that would be very interesting.
Costs of Regionalizing
Once you have an estimate on the annual savings, you can then begin to compare those savings to the cost of getting there. The cost, who pays, and how likely the solution is to produce the savings identified above will depend on the strategy you choose for harmonizing the data. I’ll be addressing these different approaches in a follow-up post, so stay tuned. When we’re done, we should have a decent model for MLSs to assess the costs and benefits (or the “bottom line”) of regionalizing their MLS data formats.