Cost-Effective Resident Acquisition · 2009. 6. 9. · 4 Cost-Effective Resident Acquisition...

©2009 Multifamily Technology Solutions, Inc. (DBA MyNewPlace.com). All rights reserved. Reproduction in any fashion without the express written permission of MyNewPlace.com is prohibited.

Cost-Effective Resident Acquisition (Hint: Think Direct Marketing)

April 2009

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Cost-Effective Resident Acquisit ion

Table of Contents About the Authors........................................................................................................................................................ 3About MyNewPlace ..................................................................................................................................................... 3Contact Information ..................................................................................................................................................... 3Executive Summary..................................................................................................................................................... 4Introduction.................................................................................................................................................................. 4Direct Marketing Techniques Applied to the Multifamily Industry ................................................................................ 5Identify Sources........................................................................................................................................................... 6Determine Common Metric........................................................................................................................................ 10Benchmark Sources .................................................................................................................................................. 16Allocate Spend (and Efforts)...................................................................................................................................... 21Repeat ....................................................................................................................................................................... 22Conclusion................................................................................................................................................................. 23Appendix A – Simple Cost per Non-duplicate (or Unique) Lead Analysis ................................................................. 24Appendix B – Advanced Cost per Non-duplicate (or Unique) Lead Analysis for Large Portfolios............................. 26

Table of Exhibits Exhibit 1: Monthly Traffic Levels for Paid Internet Listing Services ............................................................................. 6Exhibit 2: Sample Google Analytics Report ................................................................................................................. 7Exhibit 3: Illustrative Lead/Lease Generation By Source ............................................................................................ 8Exhibit 4: Leases by Marketing Source for AvalonBay................................................................................................ 9Exhibit 5: Where Renters Start Their Apartment Search – Local vs. Relocation......................................................... 9Exhibit 6: Perceived Value of Various Apartment Listing Sources ............................................................................ 10Exhibit 7: Level of Effort vs. Impact for “Cost per” Analysis (Illustrative) ................................................................... 12Exhibit 8: Example of “Cost per” Rankings by Metric and Source ............................................................................. 13Exhibit 9: Summary of Cost per Lead/Lease from Major Owner/Manager PMS Systems......................................... 13Exhibit 10: “Garbage in, Garbage Out”: Level One Guest Card to PMS Lease Data Comparison Findings ............. 14Exhibit 11: Example of Simple Cost per Lead Analysis for 10 properties.................................................................. 18Exhibit 12: Property-Specific Lead and Cost-per-Lead Data ..................................................................................... 19Exhibit 13: Example of Cost-per-Guest-Card Calculation ......................................................................................... 20Exhibit 14: Typical Lead Source Costs and Expected Volume.................................................................................. 21Exhibit 15: Example of Simple Cost-per-Lease Analysis for 10 properties ............................................................... 22Exhibit B1: Sample completed data worksheet ......................................................................................................... 27Exhibit B2: Completed Property ID tab...................................................................................................................... 27Exhibit B3: Updated tab in Source 1 Data workbook................................................................................................. 28Exhibit B4: Incomplete aggregate worksheet ............................................................................................................ 29Exhibit B5: Partially completed aggregate worksheet ............................................................................................... 29Exhibit B6: Completed aggregate worksheet ............................................................................................................ 30

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About the Authors

John Helm is the founder and CEO of MyNewPlace. John was the founding CEO of AllApartments/SpringStreet, which became the number one apartment rental and relocation site on the Internet before its sale to Homestore (NASDAQ: HOMS) in 1999. Prior to SpringStreet, John was the Chief Financial Officer and Head of Business Development for Marcus & Millichap Real Estate Investment Brokerage Co., where he headed up all finance, technology and business development activities. John was also a consultant for McKinsey & Co. for six years and a sales specialist for Coldwell Banker Commercial Real Estate Services. John holds a B.A in Economics from the University of Wisconsin and an MBA from Harvard Business School.

Vanitha Virudachalam is a Marketing Manager at MyNewPlace and an honors graduate in mathematics from University of California, Berkeley.

About MyNewPlace MyNewPlace (www.mynewplace.com) launched in May 2006, creating the largest and easiest-to-use online marketplace for apartment rentals, connecting renters and owners of all types of properties. MyNewPlace is a performance-based solution to help owners fill their vacancies. MyNewPlace has also recently launched Featured Property placement, integrated mapping and community photo and video packages to continue to help management companies fill their vacancies cost-effectively.

In addition to being an Internet Listing Service, MyNewPlace launched MyNewSite™ (www.mynewsite.com) in 2007. This full-service Web site solution was designed to help the multifamily industry cost-effectively promote, brand and drive leases to their communities for as little as $45 to $110 per month. With MyNewSite, management companies can design a corporate site that includes individual property Web sites and map-based searching capabilities.

Contact Information Shane Maddox [email protected]

415.348.2022

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Cost-Effect ive Resident Acquisit ion (Hint: Think Direct Marketing)

Executive Summary Marketing is a significant expense for owner/managers of multifamily housing. However, many advertising decisions are made without clear data on how effective different forms of advertising are. The multifamily industry can change this by using principles of direct marketing to assess which advertising methods will generate the most leads and leases for the least money. This whitepaper outlines five basic steps owner/managers can take to evaluate which sources of leads are most cost-effective: 1) Identify Sources 2) Determine Common Metric 3) Benchmark Sources 4) Allocate Spend (and Effort) 5) Repeat These basic steps can help managers identify up to 30 percent of their advertising spend that is not cost-effective. That money can then be reallocated to more efficient advertising methods, resulting in more leads and leases for the same, or possibly even less, money.

Introduction “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” This quote by John Wanamaker, considered the father of modern advertising, is heard frequently these days in our industry’s discussions of advertising effectiveness. And for good reason: The multifamily industry spends around $170 per unit yearly on marketing costs – over $50,000 annually for a 300-unit property, or $1.7 million per year for a 10,000-unit portfolio. The bulk of this spending goes to advertising, yet the typical owner/manager still struggles to determine if this money is delivering cost-effective results. Industry marketing and technology professionals spend significant time and effort trying to understand the efficiency of their marketing expenditures, not always successfully. The numbers produced internally by many owner/managers are so poor that in the end the data is often ignored, and marketing decisions are effectively made on a gut basis. Luckily, there are other industries that have made greater progress using direct marketing techniques to get at the question of advertising efficiency, and the multifamily industry can learn some simple lessons from them. Wikipedia defines direct marketing as follows:

Direct marketing is a sub-discipline and type of marketing. There are two main definitional characteristics which distinguish it from other types of marketing. The first is that it attempts to send its messages directly to consumers, without the use of intervening media. This involves commercial communication (direct mail, e-mail and telemarketing) with consumers or businesses, usually unsolicited. The second characteristic is that it is focused on driving purchases that can be attributed to a specific "call-to-action." This aspect of direct marketing involves an emphasis on trackable, measurable positive (but not negative) responses from consumers (known simply as "response" in the industry) regardless of medium.

These basic steps can help managers identify up to 30 percent of their advertising spend that is not cost-effective.

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If the advertisement asks the prospect to take a specific action, for instance call a free phone number or visit a website, then the effort is considered to be direct response advertising.

The underlined portion of this definition, concerning measuring the “direct response” to an advertisement, is most relevant to the multifamily industry. Indeed, most online marketers today are heavily focused on measuring and tracking the results of their online advertising. As a result, entire industries have emerged to serve their needs, from specific lead-generation businesses such as QuinStreet and NexTag to software and/or analytics vendors such as Omniture and Efficient Frontier. Of course, no one company has done more to advance this approach to advertising than Google, with its Cost per Click-based pricing and transparent marketplace for qualified Web traffic. Perhaps the best example of a company leveraging direct marketing techniques to build its business is the Apollo Group’s University of Phoenix (UoP), the largest alternative education company in the world. This $2.7 billion revenue behemoth, with over 200 physical campuses and extensive online learning capabilities, has been a Top-20 online advertiser for most of the last decade. For example, ComScore reports that it was the No. 2 online advertiser in June 2008, with more than 4.7 billion ad impressions that month alone. Much like the multifamily market, the UoP’s target audience is quite broad: It offers degrees ranging from high school diplomas to Ph.D.’s and targets a wide range of individuals seeking to broaden their educational horizons, from youth to working adults. While a large market is enviable, it can make targeted and cost-effective direct marketing more challenging. The UoP is known for relentlessly monitoring and optimizing every advertising channel and campaign. It measures a host of key performance indicators, including cost per lead, cost per application and ad spend ROI, based on actual tuition billed and collected. Its senior management sets acquisition cost targets by channel, and its marketing team is held strictly accountable for achieving those goals.

Direct Marketing Techniques Applied to the Multifamily Industry This whitepaper outlines direct marketing techniques that any multifamily marketing professional can use to acquire new residents in the most cost-effective manner possible. We will discuss the basic steps to developing a cost-effective resident-acquisition plan and outline more sophisticated and analytical approaches that can increase the accuracy of the analysis and the cost effectiveness of the plan. Even taking the simplest approach outlined below should yield substantial results for the typical manager. For example, we have worked with the heads of marketing for several owner/managers in implementing the analytical approach recommended in this whitepaper. In every case, the owner/ manager has been able to identify 20 percent to 30 percent of their advertising spend that was simply not cost-effective. In many cases, they were able to cut this spend, redeploy half the “saved” dollars and replace, or even increase, the number of leads and leases generated. In fact, according to Kevin Thompson, vice president of marketing for AvalonBay, by consistently taking such a quantitative approach to analyzing the effectiveness of AvalonBay’s advertising spend, AvalonBay has been able to decrease its advertising budget every year for the past five years while still increasing leads and leases. What follows is a fairly simple way to employ basic direct marketing techniques. We will give more details on each of these steps in later sections.

1. Identify Sources: Consider all potential lead and lease sources.

2. Determine Common Metric: Once you have identified all your sources, choose a consistent metric for tracking them and measuring them against each other. This metric should be the one you are most confident you can consistently measure, track and analyze for the greatest number of potential sources.

“AvalonBay has been able to decrease its advertising budget every year for the past five years while still increasing leads and leases.”

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3. Benchmark Sources: Once you have an accurate way to measure your sources, benchmark them against each other using that metric. For example, if the metric is “cost per unique lead” (not counting multiple leads from the same consumer), then measure each source by that metric for a similar time period. This time period should be long enough to be statistically relevant1 but not so long that changes over time will be missed or understated. We have found that a quarter will usually suffice; the additional accuracy gained by using a full year is usually offset by the changes in the efficiency of each source over that one-year period.

4. Allocate Spend (and Efforts): With relatively accurate data (with stress on the word relatively, as perfection is usually the enemy of action), you can then simply allocate your spend from the most cost-effective to the least cost-effective sources for each property until your requirements are met. For example, if you have determined that a given property needs 100 leads to fill the next month’s anticipated vacancies, then you would allocate your spend from the most cost-effective source to the least, until you reach 100 expected leads.

5. Repeat: A good direct marketer does this on an ongoing basis, looking at the data and adjusting monthly, weekly or even daily. However, given the difficulty of gathering and analyzing the data in the multifamily industry, quarterly or even annual analysis should be sufficient. Abbreviated versions of the analysis can be done more frequently, such as monthly, to make sure no one source has suddenly become cost prohibitive.

Identify Sources When identifying sources of potential leads and leases, be as comprehensive as possible. Group the sources by type to help you calibrate their quality later. Be sure to apply the MECE principal (mutually exclusive, collectively exhaustive), making sure that each group represents only sources that can be fully categorized in that manner. This will ensure that you do not double-count the impact of any sources in your analysis. Typically, the sources of leads will break down into the following groupings:

1. Online-Only Sources: Sources that are visible only online, increasingly the largest source of leads for leading owner/managers:

a. Paid Internet Listing Services (ILS): Major sites such as Rent.com, Apartments.com and MyNewPlace.com, as well as many of the smaller or regional services.

Exhibit 1: Monthly Traffic Levels2 for Paid Internet Listing Services CY2008

Source: Hitwise

1 A data set of 100 results per source will yield a confidence interval of +/- 15 percent, meaning that your long-term results should

average within 15 percent of those calculated. 2Graph values are the percentage of all U.S. web traffic visiting that ILS in that month, as measured by Hitwise using its panel of

25 million Internet users.

“…apply the MECE principal (mutually exclusive, collectively exhaustive)”

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b. No-Cost Internet Listing Services/Classifieds: Sites such as Craigslist and smaller regional and local sites. Note that these free sites often require much more effort on the part of your marketing team/leasing staff to post and maintain your listings. (For example, Craigslist does not allow data feeds/automatic posting, so you must post each listing manually.) When analyzing the efficiency of Sources such as Craigslist, you should also factor in the time required to maintain these listings, which across a large portfolio can easily keep an employee busy almost full-time.

c. Your Apartment Marketing Site3: Sources that drive traffic to your company website. Ideally, you would track the following groupings of leads to your site:

i. Search Engine Marketing (SEM): Cost per Click search advertising on Google, Yahoo!, MSN and others. Given the lack of concentration of properties in a given market for most managers, Cost per Click advertising is usually cost-prohibitive for all but the largest owner/managers.

ii. Online Marketing: Banner, text link and other forms of online advertising, typically priced on a cost per thousand impressions (CPM). While marketing via social media sites has garnered tremendous buzz, non-SEM online marketing is extremely difficult to make ROI positive.

iii. Referral Traffic: Traffic from posting your properties on sites such as Craigslist, non-pay-for-performance ILS’s and other referral sites.

iv. Search Engine Optimization: Traffic from natural, non-paid positions on search engines.

v. Organic (Direct Traffic): Traffic from people typing in your URL.

Exhibit 2: Sample Google Analytics Report September 2008

Source: Disguised MyNewSite Client Reporting (Google Analytics), 2008

2. Print/Online Sources: Print publications that also have Internet sites. Since the print

publication drives traffic to the vendor’s Internet site, and sometimes visa versa, it is usually worthwhile to analyze results by grouping them separately from the Internet-only ILS’s. The largest are For Rent, Apartment Guide and Apartment Finder.

3. Banners/Signage: All visible outdoor advertising at the property, still a very cost-effective lead source.

3 Note: For a primer on Apartment Marketing Websites, see the previous whitepaper published by the NMHC titled: “Multifamily Marketing in the Internet Age.”

“When analyzing the efficiency of Sources such as Craigslist, you should also factor in the time required to maintain these listings.”

“Given the lack of concentration of properties in a given market for most managers, Cost per Click advertising is usually cost-prohibitive for all but the largest owner/managers.”

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4. Other: Sources that may not initiate contact via phone and email before visiting, such as referrals and drive-bys. This grouping is more difficult to track on a lead basis.

In general, leads from advertising sources should drive 60 percent to 70 percent of your lease volume, with the other 30 percent to 40 percent from sources such as referrals and drive-bys that typically are not tied to a direct response marketing effort. The following exhibit illustrates the typical lead breakdown for a large owner/manager that is aggressively using the Internet.

Exhibit 3: Illustrative Lead/Lease Generation By Source

Source: MyNewPlace, Compete, Inc. 2008

Kevin Thompson of AvalonBay has generously shared with the industry AvalonBay’s lease source breakdown by major category, which broadly corresponds to the previous exhibit. It should be noted that AvalonBay has a very aggressive Internet strategy, developed after years of careful analysis of lead-acquisition costs by advertising source. This direct marketing approach, with its emphasis on analytics, has made clear that for AvalonBay, Internet-based sources generate some of it’s lowest-cost leads and leases. We would argue that while AvalonBay’s lead/lease acquisition program may at this point be more online-oriented than most, it is likely indicative of the industry’s direction.

Qualified Leads by Source Type (calls and emails that

result in a guest card)

Lease Volume

by Source

Online Only

75-80%

Banners/Signage

2.5%

Other

~5%

Print/Online

12-18%

Online Only

~50%

Print/Online 8-12%

Drive-by 12-17%

Referral 12-15%

Other 5-15%

Advertising Leads typically drive ~60% of Lease Volume

“…leads from advertising sources should drive 60 percent to 70 percent of your lease volume.”

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Exhibit 4: Leases by Marketing Source for AvalonBay 2004 to 2006

Source: AvalonBay Communities, Inc.

To illustrate this trend, we have reprinted the following two exhibits from the whitepaper published by the National Multi Housing Council (NMHC), titled “Multifamily Marketing in the Internet Age.” Exhibit 5 indicates that 54 percent to 72 percent of renters (depending on whether the move is local or long distance) start their search online today.

Exhibit 5: Where Renters Start Their Apartment Search – Local vs. Relocation

Source: ”Multifamily Marketing in the Internet Age,” NMHC, 2008. Data generated by a survey of over 600 renters who had moved within the past six months who had access to the Internet.

The report also shows that consumers regard the Internet as the most valuable source when searching for an apartment. This behavior also holds true for other research-intensive purchases, such as buying a car, taking a job or buying a home. Interestingly, consumers value the Internet more even than advice from family and friends when making a rental decision. This suggests that they believe there is enough data available online to lead to a conclusion.

31

9

21

16 13

2

37

6

20

15

11

1

44

4

18 14

11

1

51

2

16

12 9

1 0%

10%

20%

30%

40%

50%

60%

Internet Print

Guides

Drive-By/

Signage

Referral

Other

Resident

Referral

Newspaper

2004 2005

2006 2007

10% 20% 30% 40% 50% 60% 70%

Other

Apartment Locator Service

Real Estate

Brokers

Referrals from

Family or Friends

Apartment Listing Circulars/

Magazines

Newspaper

Listings

The

Internet

3%

2%

7%

13%

21%

54%

6%

2%

3%

4%

4%

9%

72%

0%

0% 80%

Same MSA New MSA

“…54 percent to 72 percent of renters (depending on whether the move is local or long distance) start their search online today.”

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Exhibit 6: Perceived Value of Various Apartment Listing Sources

Source: “Multifamily Marketing in the Internet Age,” NMHC, 2008

However, while many owner/managers today are focused on using the Internet to cost-effectively supply the majority of their leads, each should analyze their own properties and portfolio, as results may vary by market and advertising source. For example, many clients tell us that print still works quite well in certain markets – including, somewhat counterintuitively, some college towns.

Determine Common Metric Once you have identified all of your sources and gathered the reporting available on each, you need to determine the appropriate common metric for benchmarking these advertising sources.

We recommend applying the 80/20 rule to both the number of sources included and the level of analysis done. For example, as Exhibit 3 illustrates, your advertising lead volume should generate 60 percent to 70 percent of your leases. Tracking the leads associated with the remaining 30 percent to 40 percent is difficult: Drive-bys and referrals often do not generate phone or email leads. In addition, the cost for a lead in these cases is not as relevant. Therefore, we recommend that you restrict your analysis to those lead/lease sources that constitute the majority of your lease volume and controllable advertising spend and can be more easily tracked and analyzed. You can always expand your analysis later to include lease source costs that are not included in this group, such as referrals.

There are four main metrics for benchmarking a lead/lease source’s cost effectiveness. Here are the pros and cons of each, and when it is appropriate to use them:

1. Cost per Lead/Unique Lead: Phone calls and emails to property.

a. Pro: Easy to track, measure and benchmark.

b. Con: Does not differentiate by quality or measure activity not originated with a call/email.

c. Recommendation: Best used as a first step in measuring cost efficiency of spend, but needs to be calibrated for quality.

2. Cost per Guest Card: Cards completed by either a call center or on-site leasing staff after speaking or corresponding (by email) with a prospect enquiring about renting.

a. Pro: A better measure of “qualified” leads, since vendor and non-prospect calls are weeded out.

b. Con: Typically successful only for companies using a call center or comprehensive lead-tracking system.

60%

80%

0%

20%

40%

Apartment

Listing

Circulars/

Magazines

Apartment

Locator

Service

Real

Estate

Brokers

Signs on

Properties

Newspaper

Listings

Referrals

from

Family/

Friends

The

Internet

Very valuable Valuable

“We recommend applying the 80/20 rule to both the number of sources included and the level of analysis done.”

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c. Recommendation: Great initial measure of lead quality if you are confident all leads are captured and screened, resulting in a comprehensive view of lead sources, i.e., if you use a call center such as Level One or Crossfire, or a lead-tracking product that captures all inbound leads (and when the leasing staff or a call center weeds out non-prospect calls/emails).

3. Cost per Appointment: Leads that result in an appointment to tour the property.

a. Pro: A more refined view of a qualified lead.

b. Con: Works effectively only with a call center and still misses unscheduled appointments driven by that particular advertising source, such as walk-ins and drive-bys. This measure becomes especially distorted if a particular source sends a high volume of email leads, as they tend to yield fewer appointments relative to the ultimate number of leases they generate.

c. Recommendation: Best used as a calibrating point for lead quality, but not by itself, as it misses leases not generated via an appointment.

4. Cost per Lease: Actual signed leases as reported by Property Management Software (PMS) or, better, via name-matching of “leads” (or guest cards) against move-ins.

a. Pro: Best measure of quality, if generated via a name-matching exercise.

b. Con: Heavily reliant on human data entry, which has been proven to be seriously flawed in the case of data from a PMS. It also takes a long time to generate a statistically valid data set.

c. Recommendation: Data from a PMS should not be used given serious documented quality issues. Rather, matching move-in data against leads/guest cards should be done on a regular basis to determine “lead close rates,” which can be used to calibrate cost-per-lead metrics.

Overall, the level of effort increases significantly with each step you take to improve the level of accuracy in the data. The following chart illustrates the level of effort versus the expected “impact” in terms of certainty that we have found to be the case when doing this analysis.

“Data from a PMS should not be used given serious documented quality issues. Rather, matching move-in data against leads/guest cards should be done on a regular basis to determine “lead close rates.”

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Exhibit 7: Level of Effort vs. Impact for “Cost per” Analysis (Illustrative)

Source: MyNewPlace 2009

We have found that while a more exhaustive analysis will result in a more informed picture of the cost efficiency of each lead source, the relative ranking of a given ad source does not usually change significantly with each more accurate step. As the following exhibit illustrates, in a survey of 10 properties, each source roughly maintained the same relative ranking regardless of the measure. The one exception was cost per visit set, which is usually overstated for sources that sent a high proportion of email leads4.

4 Data are actual results for an actual owner/manager.

MyNewPlace Confidential 8

Cost per Unique Lead

Lease Data:

Name Matching and Analysis

Level of Effort Expected Impact

Basic Data Collection (must be completed regardless): Leads and Cost

Cost per Lease

Cost per Guest Card

Cost per Lead

Guest Card Data:

Matching And Analysis

Unique Leads:

Application and Analysis

45%

25%

15%

15%

15%

40%

5%

40%

Cost-per-Lead Analysis

“...the relative ranking of a given ad source does not usually change significantly with each more accurate step (of analysis).”

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Exhibit 8: Example of “Cost per” Rankings by Metric and Source 10 properties, June & July 2008

Source: MyNewPlace (based on client data), 2008

Attempting to increase the level of accuracy beyond a simple cost-per-unique-lead calculation, if not done properly, can greatly increase the risk that the conclusions will be inaccurate. This is especially the case if the data to determine cost per lease is coming from a PMS product that relies on leasing staff to record a lead/lease source. For example, in a survey of major owner/managers conducted last spring in conjunction with the National Association of Home Builders (NAHB), it was found that the cost-per-lead and cost-per-lease data from a group of owner/manager’s PMS systems was so distorted that it was not actionable. Survey participants were quoting cost-per-lead data for a single source as high as $241 across an entire portfolio of properties, and portfolio-wide cost-per-lease data as high as$4,0005! Obviously, these owner/managers had already reached the conclusion that this data was not accurate. Therefore, most were continuing to make their advertising spending decisions based on past experience, their field manager’s instincts or their “gut.”

Exhibit 9: Summary of Cost per Lead/Lease from Major Owner/Manager PMS Systems Spring 2008

Source: Survey of major owner/manager internal cost per lead/lease data from PMS systems, conducted in conjunction with NAHB, Spring 2008.

5 Note: You can, and often do, find costs this high for a single property, especially in a large, 100+ property portfolio. But never have costs this high been found for an entire portfolio when the analysis has been done correctly.

$30

$40 $139 $109 $2,158

$35

$59

$49

$29 $43

$13 $21

$12 $14

$0 $20 $40 $60

Source 5

Source 6

Source 4

Source 3

Source 2

Source 1

Cost / Unique Lead

$0 $20 $40 $140

Cost / Guest Card

$148

$94

$61

$78

$94

$0 $50 $100 $150

Cost / Visit Set

$605

$758

$546

$381

$467

$0 $250 $500 $2,250

Cost / Lease

PMS Cost per Lead PMS Cost per Lease

$20

$61

$26 $8 $23 $8

$97

$52 $27 $25

$88

$143 $112 $122

$0

$50

$100

$150

$200

$250

1 2 3 4 5 6

$241

$182

$162

$985

$1,105

$619

$266 $298

$687

$1,190

$4,062

$1,012

$373 $305

$1,249

$0

$100

$200

$300

400

500

600

700

1 2 3 4 5 6

$1,000

$2,250

$3,500

$5,000

$85$118 $111

$214$240

$128

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

PMS Cost per Lead PMS Cost per Lease

$20

$61

$26 $8 $23 $8

$97

$52 $27 $25

$88

$143 $112 $122

$0

$50

$100

$150

$200

$250

1 2 3 4 5 6

$241

$182

$162

$985

$1,105

$619

$266 $298

$687

$1,190

$4,062

$1,012

$373 $305

$1,249

$0

$100

$200

$300

400

500

600

700

1 2 3 4 5 6

$1,000

$2,250

$3,500

$5,000

$85$118 $111

$214$240

$128

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

Sourc

e

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Research by Level One, a leading call center vendor in the industry, has confirmed this accuracy problem with internally generated lead and, particularly, lease cost data from PMS systems. Level One typically will conduct a “guest card name-matching exercise” with a new client after six to nine months in which they match all the names on the guest cards they process for a given client with the client’s list of renters that moved in during the same time period. This exercise allows Level One and the client to determine the effectiveness of various lead sources by allowing them to accurately measure close rates by lead/lease source. When doing this analysis, Level One typically has found significant discrepancies between their data and what the client has in their PMS. In fact, typically, only about one-third of the leases in the PMS match the original source that Level One digitally recorded when they first processed the lead. That means that two-thirds of the leases in the PMS are sourced incorrectly. Todd Katler of Level One has shared the following exhibit in a number of presentations, which details their findings.

Exhibit 10: “Garbage in, Garbage Out”: Level One Guest Card to PMS Lease Data Comparison Findings

Source: Level One, 2008

This is not surprising when you think about everything that the typical leasing associate is responsible for. More often than not, when a prospect arrives at the property for a tour or to sign a lease, the associate will simply start a new guest card in the PMS, rather than looking for a preexisting one. Even if the prospect did not have a preexisting guest card, the associate is typically too busy or focused on selling to ask “how they found us,” and thus in many cases does not fill that field in on the form until after the prospect has left. Then the associate fills in a “safe” field such as “Craigslist” or simply “Internet.” Finally, even if the leasing associate remembers to ask “how you found us” during the appointment, call center vendors such as Level One have found that the prospects don’t place a high degree of importance on the answer, as they have no incentive to share the right information.

Most PMS systems rely on the leasing office staff to input the source to a given lease

•! Only 32.6% of manually entered sources in Property Management Software (PMS) matched the digitally recorded source of Level One

•! Of 13 ad sources tracked, 11 created more leases than they were credited with.

!!One source was only given credit 26.3% of the time

•! Over-reported sources include:

!!Craigslist (40% more credit)

!! Internet (1,300% more credit)

!!22.3% of leases incorrectly attributed to “Drive-By”

•! Of actual appointments that turn into leases, 64.5% of the sources were incorrectly attributed in the PMS (despite being electronically transmitted with the appointment)

Source: Level One, 2008

A recent analysis by Level One found significant variances:

“Garbage In = Garbage Out”

“… two-thirds of the leases in the PMS are sourced incorrectly.”

“More often than not, when a prospect arrives at the property for a tour or to sign a lease, the associate will simply start a new guest card in the PMS, rather than looking for a preexisting one.”

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Why Lead to Lease Close Rates generated via a name-matching exercise will always be systematically understated

A name-matching exercise is the best way to calculate the lead-to-lease close rate for a given portfolio, however even this procedure will still systematically understate the true close rate for a given source for the following reasons: 1. Not all prospects from a given source initiate contact via a phone call or email before visiting the property – indeed, out of a random sample of 1,000 renters who submitted a valid rebate claim, we found that only 50% of the claimants had electronically contacted that property. 2. Name-matching doesn’t work if the person who contacts the property isn’t the ultimate lease signatory, such as a partner, or relative helping someone do a search. 3. Typically one will conduct a name-matching exercise for a large data set over a multi-month period, matching say, all leads generated from January through June against move-ins over the same time period, or possibly adding an extra month or two on the backend – say through July or August. However, as the average renter starts searching 50 days before they move (meaning over 50% of renters are looking to move sometime after 50 days from when they start their search), the guest cards generated in the latter months of the survey set have a lower likelihood of matching given that many of those prospects may not have signed a new lease yet. Therefore, a good rule of thumb is to at least double any close rate calculated in a name matching exercise if you want to get something resembling a true close rate for a given source.

In other cases, clients have not updated their procedures in years, which can also drive erroneous data. For example, one client‘s corporate marketing staff was disturbed at the number of “walk-ins” that their on-site leasing staff was reporting. When they checked their training manuals, they found the manual said that if the client walked into the leasing office (presumably without an appointment), they should be listed as a walk-in (as opposed to asking them how they found the property). In this case, the staff was doing exactly what they had been told to do, but it was skewing all of their internal numbers.

Increasingly, Level One’s more sophisticated customers rely on this “name matching” data to measure the relative quality of their leads, as they have come to realize that the methodology Level One uses results in much more accurate, and thus actionable, data (sources listed on their original guest cards are hard-coded based on source-specific email addresses or 800 tracking numbers).

Based on these findings, the cost-per-lead (or lease) data found in a PMS simply should not be used. It will invariably result in the wrong decisions and could end up costing an owner/manager thousands, if not tens of thousands, of misallocated advertising spend per property. Rather, if owner/managers are using Level One (or another call center vendor), they should periodically request that their call center vendor do a name-matching exercise and use the close-rate data from that effort to calibrate their lead quality and determine a more realistic cost per lease by source. However, even close rates determined via a name-matching exercise will be systematically understated (see adjacent box), and thus should only be used as a directional or relative measure.

16


Benchmark Sources Based on what Level One and other lead-tracking vendors have learned about the quality of data contained in PMS systems, we recommend that everyone start with the simplest way of doing this analysis – cost per unique lead, which typically will be enough to allow you to force rank a given set of lead/lease sources with relative certainty. This analysis is very easy, and many leading companies in the industry already do it. And since each ILS provides relatively accurate reports, you do not need any sort of lead-tracking product to perform the analysis. Rather, you simply adjust their reporting to account for duplicate leads and add in your cost data. If you do this analysis for the major ILS and print guides, you should cover roughly 65 percent to 80 percent of your leads.

The next biggest lead source is likely your own website. To measure the leads from that source, you will need accurate reporting provided either by your website vendor, internal IT department, or call center/lead-tracking vendor. For simplicity’s sake (and following the 80/20 rule), we will restrict our analysis to the major ILS’s for now. However, the same principles apply, and it is easy to add in your own website’s cost per lead if you have the data handy. We strongly recommend you also do this cost per lead analysis for your own website as many companies over-invest in their sites relative to the leads they generate.

What follows is a high-level description of how to do this analysis for all of your major “paid” sources, illustrated using actual data on 10 representative properties owned by a major owner/manager who let us use their data for this exercise. For a more detailed step-by-step description, complete with examples of spreadsheets, please refer to Appendix A and the even more in-depth Appendix B.

Why Calculating a cost per lead for your own AMS, or Corporate Website is important

Apartment Marketing Sites (AMS), or Corporate Websites can typically generate anywhere from 2 to 30 leads a month per property (some have reported generating significantly more), depending on how well they’re designed, set up for SEO, and marketed. Additionally, your ability to drive traffic to your AMS will have a lot to do with where the properties are located. For example, properties in high-barrier, Internet-savvy markets like San Francisco will get far more traffic than properties on an AMS in softer, rural markets. Owner/managers should be careful not to over-invest in their AMS as it will make their cost per lead too high. For example, spending $300 a month for a high-end website is only a good idea if you think that that site has the potential to generate a minimum of 15 to 20 leads a month. If you are using an external vendor to power your AMS, ensure you are getting the reporting (email and 1-800 call tracking) to see if the leads it is generating justify the cost. If you are operating your own AMS internally, make sure the resources allocated to its ongoing operation (for example, programmers, consultants, webmaster, hosting) are justified by the lead volume the site is generating. To do this, simply take the monthly cost of all of these dedicated resources and divide it by the monthly lead volume generated to determine your cost per lead. If it is over $20 to $30 a lead, you may want to consider outsourcing to a lower cost provider, as there are options in the market for as little as $50 per property a month.

Simple Cost-per-Unique-Lead Analysis: This is the recommended approach for all companies. If you use a call center we will discuss how you can calibrate these results in a later section.

1. Step One: Modify individual ILS/Print Guide reports to reflect non-duplicate leads and load into an Excel spreadsheet. You can do this for a single month or several; the following analysis is based on two months’ data, June and July of 2008. Different ILS’s and print guides report their lead data differently, and you need to get all of them on an equal footing for comparison purposes. The steps are as follows:

a. Isolate the phone and email lead columns in each ILS report. Each vendor will provide (or make available online) an Excel formatted file (or .csv that can be converted to Excel) with your activity by property. Gather those reports together and identify the above-mentioned columns.

“…many companies over-invest in their sites relative to the leads they generate.”

17


b. Create a master spreadsheet with all of your properties and then load the lead data into it, being careful to match up by property if all properties do not use the same service, so that you have one spreadsheet with three columns for each marketing source for each property: Phone Leads, Email Leads and Total Leads.

c. De-dupe leads by lead source. To do this, you need to know how each vendor reports leads in its reporting. What follows is a brief summary of how the various vendors report leads:

i. Reports gross and unique leads: MyNewPlace

ii. Reports unique leads only: Rent.com

iii. Report gross leads only (includes multiple leads sent by the same user): All other sources

In the case of Rent.com, you can use their lead numbers as is; in the case of MyNewPlace, you should use the unique lead numbers only; and for other vendors, you should calibrate the leads to account for duplicate leads. To do this, take a one-month sample of actual leads for a set of properties and calculate the ratio of gross leads to unique leads to determine the fraction by which you need to lower their leads. For example, if a vendor reported 15 leads for a given property but three individuals sent two leads each (identified by either the same email address or same phone number), then you actually received 12 unique leads, for a unique-lead ratio of 80 percent. Unfortunately, there is no way to de-dupe for the same individual calling and emailing. However, as you cannot do this with any vendor, the data will still be consistent across all sources.

d. Total the unique leads in a new “Unique Leads” or “De-duped Leads” column.

2. Step Two: Next, add the total monthly cost for each property by source. Do not use your internal general ledger data, as we have found that many companies misallocate expenses and date the entries so that for some months you will have double the cost, and some none. Use your contracted pricing from the source (vendor) instead as it will be more consistent. Place this monthly figure in the new column titled “Total Cost.” Do not forget to add the cost of any additional products such as featured placement or outbound email programs.

3. Step Three: Create a new column titled “Cost/Unique Lead,” and divide the monthly cost by the total leads to come up with a consistent cost per unique lead across all of your sources. Hide all columns except for the Total Unique Leads, Total Cost and Cost/ Unique Lead columns.

Once completed, you should have a spreadsheet that resembles the following, which we created using actual data from the above referenced 10 properties:

18


Exhibit 11: Example of Simple Cost per Lead Analysis for 10 properties June & July 2008

Source 1 Source 2 Source 3

Property Name Unique Leads Cost

Cost / Unique Lead

Unique Leads Cost

Cost / Unique Lead

Unique Leads Cost

Cost / Unique Lead

Property A 31 $378 $12.19 106 $382 $3.59 29 $500 $17.24

Property B 26 $351 $13.50 69 $1,532 $22.15 28 $500 $17.86

Property C 26 $351 $13.50 67 $382 $5.72 24 $500 $20.83

Property D 24 $324 $13.50 37 $892 $24.43 25 $500 $20.00

Property E 18 $243 $13.50 138 $1,946 $14.07 32 $500 $15.63

Property F 15 $203 $13.50 8 $1,103 $139.19 16 $500 $30.91

Property G 13 $176 $13.50 82 $1,532 $18.71 8 $500 $58.84

Property H 12 $162 $13.50 24 $1,300 $54.54 46 $500 $10.87

Property I 11 $149 $13.50 11 $226 $20.40 21 $500 $23.81

Property J 8 $108 $13.50 80 $2,299 $28.64 11 $500 $45.45

Source: Survey of 10 properties, June & July 2008.

With this spreadsheet, it is easy to sort by each vendor’s cost-per-unique-lead column to quickly determine which sources work best for each property. We have shown the same data graphically to illustrate the differences better.

19


Exhibit 12: Property-Specific Lead and Cost-per-Lead Data June & July 2008

Source: MyNewPlace Client Data, June & July 2008.

8

11

12

13

15

18

24

26

26

31

0 20 40 60 80 100

Property J

Property I

Property H

Property G

Property F

Property E

Property D

Property C

Property B

Property A

11

21

46

8

16

32

25

24

28

29

0 20 40 60 80 100

80

11

24

82

8

138

37

67

69

106

0 20 40 60 80 100 150

$108

$149

$162

$176

$203

$243

$324

$351

$351

$378

$0 $200 $400 $600 $800 $1,000

Property J

Property I

Property H

Property G

Property F

Property E

Property D

Property C

Property B

Property A

$500

$500

$500

$500

$500

$500

$500

$500

$500

$500

$0 $200 $400 $600 $800 $1,000

$2,299

$226

$1,300

$1,532

$1,103

$1,946

$892

$382

$1,532

$382

$0 $200 $400 $600 $800 $1,000 $3,000

$13.50

$13.50

$13.50

$13.50

$13.50

$13.50

$13.50

$13.50

$13.50

$12.19

$0 $20 $40 $60 $80 $100

Property J

Property I

Property H

Property G

Property F

Property E

Property D

Property C

Property B

Property A

$28.64

$20.40

$54.54

$18.71

$139.19

$14.07

$24.43

$5.72

$22.15

$3.59

$0 $20 $40 $60 $80 $100 $150

$45.45

$23.81

$10.87

$58.84

$30.91

$15.63

$20.00

$20.83

$17.86

$17.24

$0 $20 $40 $60 $80 $100

Lead Volume

Total Cost

Cost Per Lead




Cost Effective Resident Acquisition

20


As the above analysis shows, different lead sources perform differently for different properties. This is why it is difficult to say with absolute certainty that one source always works better than another.

Guest Card Analysis: If you use a call center or lead-tracking product, modifying the above analysis to include guest cards is very easy. The added information provided by your call center/lead-tracking vendor also allows you to calculate the efficiency ratio (number of leads that convert to a guest card) of each lead source. What follows is a quick demonstration of how to do this analysis as illustrated with the 10 properties from the previous example.

1. Add in Guest Card Data: Your call center/lead-tracking vendor should provide reporting for each property, typically monthly. Simply add a new column to your Cost per Unique Lead spreadsheet, titled “Guest Cards,” and for each source, by property, add its data.

2. Calculate “Cost per Guest Card” and “Efficiency Ratio”: Take your preexisting cost data and divide it by the number of guest cards to determine a new “Cost per Guest Card” metric. Additionally, divide the number of guest cards by the number of unique leads reported by each vendor to come up with an “efficiency ratio” of Unique Leads to Guest Cards. This metric helps you understand the percentage of unique leads from a specific vendor that are actually prospective residents. The exhibit below shows this data in aggregate for the 10 properties analyzed earlier.

Exhibit 13: Example of Cost-per-Guest-Card Calculation 10 properties, June & July 2008

Source: Survey of 10 properties, June & July 2008.

However, as the above exhibit demonstrates, on a property-by-property basis, certain anomalies can present themselves, such as the property that generated 106 unique leads, but only 16 guest cards. Often, circumstances like this will indicate a data gathering or operational problem that needs to be corrected, such as a given property not having its leads routed properly to the call center vendor (these sorts of errors typically occur when a new property is acquired, or a new source is set up). Obviously, until the issues surfaced by these data anomalies are understood, decisions dependent upon the analysis should be put on hold.

Calibrating for Appointments: This process works only if you use a call center that fields all of your calls and sets appointments. Even then, we do not recommend using this measure to judge a source, as it is incomplete. It tends to overstate the effectiveness of sources that generate more calls relative to emails, as calls generally result in more appointments than emails. Or, to put it another way, since emails generate fewer appointments relative to the leases they ultimately generate (i.e. relatively more people that email lease without setting up an appointment first), this metric can cause you to make the wrong decisions regarding the effectiveness of a given source.

However, it is worth noting that today, most owner/managers still experience higher lead-to-lease close rates from phone calls than emails, simply because prospects that call are more easily engaged and can thus be converted more efficiently by the leasing staff. Over time, we expect the industry will learn better ways to follow up and convert email leads, thus improving their close rates. Indeed, some multifamily industry marketing executives believe that in the long run, email leads can be made much more valuable through customized relationship-building campaigns via email and phone.

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“…different lead sources perform differently for different properties.”

“Using appointments as a metric tends to overstate the effectiveness of sources that generate more calls relative to emails.”

21


Adjusting for Lease Close Rates: As mentioned earlier, if you use a call center that both fields a call with a live person (and thus appends a name to a phone lead) and digitally hard codes a source onto your guest card (populated with information either gathered during the call or taken from the fields completed on an email form), you can conduct a name-matching exercise to get close rates by type of guest card (in the case of Level One or Crossfire), or at least by email lead in the case of a lead-tracking product.

The advantage of this additional information, besides the ability to determine a more accurate relative cost per lease, is that you can see the quality of individual leads provided by each vendor in terms of completed guest cards and, ultimately, close rates. Unfortunately, given the relatively small number of leases generated by any one source in a given month (or even several months) for a particular property, this data is statistically useful only at an aggregate level – across all your properties. However, you can take the overall close ratios and drive them back down to a property level using the overall averages –not a perfect approach, but better than using the actual data on a property-by-property basis, as small numbers can skew the results. Exhibit 15 on page 22 illustrates this process of applying portfolio-wide unique lead-to-lease close rates from a name-matching exercise across the same 10 properties discussed previously.

Allocate Spend (and Efforts) Once you have the final data, allocating your advertising spend is relatively straightforward. For a given property, simply determine the number of leads required from paid sources after anticipating leases from lower-cost sources such as resident referrals, banners/signage and your own Apartment Marketing Site. Then add in the paid sources, lowest-cost to highest-cost, until you project that you will have enough leads to generate the lease volume needed for that month (based on expected close rates).

The following exhibit shows the typical hierarchy in terms of lead volume and cost, graphically illustrating the point made above.

Exhibit 14: Typical Lead Source Costs and Expected Volume

Source: MyNewPlace, 2009

Advertising Sources Resident Contacts (leads)

Highest Cost Per

Lead (Search Engine

Marketing)

Higher Cost

Per Lead

(Print, Newspaper)

Lowest Costper Lead

(Internet Listing Services, Resident Referrals)

Free or Minimal Cost Per Lead(Craigslist, Property Websites,

A-frames/Banner)

• Average of 10-75 total leads per month

• Typically less than $5 per lead

• Average of 50-100 total leads per month (depending on # of sources)

• $10-25 per lead

• Leads vary dramatically based on concentration of properties

• $25 or more per lead

• Average of 30-80 total leads per month

• $15-40 per lead

“…these close rates are likely understated by as much as 50%, and therefore should be used for relative comparison purposes only.”

22


Repeat Given the difficulty of gathering and analyzing the data, we recommend doing the simple cost-per-lead analysis monthly. Once you have the initial spreadsheet built and become familiar with the methodology, the entire exercise should not take more than a few hours, especially if your various lead sources cooperate. In fact, some larger owner/managers actually produce their own spreadsheet, then require their vendors to fill in the unique lead and cost columns. Then all they need to do is spot-check the data to ensure each vendor is reporting the leads accurately (i.e. unique vs. gross, which includes duplicate emails and phone calls), and then create the cost-per-lead calculations.

Then, annually or semiannually, owner/managers using a call center such as Level One or Crossfire can do a name-matching exercise to calculate lead close rates and ultimate cost per lease by vendor to calibrate their monthly simple cost-per-lead analysis. Adding the average close rate (from the semi-annual or annual name-matching exercise) to the simple cost-per-lead spreadsheet to generate a cost-per-lease figure is more than adequate. Even that exercise probably won’t change the answer much, as the following chart illustrates:

Exhibit 15: Example of Simple Cost-per-Lease Analysis for 10 properties June & July 2008

Source One

Property Name Unique Leads Cost Cost / Unique Lead

Expected Close Rate Cost/Lease

Property A 31 $378 $12.19 4.2% $290 Property B 26 $351 $13.50 4.2% $321 Property C 26 $351 $13.50 4.2% $321 Property D 24 $324 $13.50 4.2% $321 Property E 18 $243 $13.50 4.2% $321 Property F 15 $203 $13.50 4.2% $321 Property G 13 $176 $13.50 4.2% $321 Property H 12 $162 $13.50 4.2% $321 Property I 11 $149 $13.50 4.2% $321 Property J 8 $108 $13.50 4.2% $321

Source Two



Property A 106 $382 $3.59 2.8% $128 Property B 69 $1,532 $22.15 2.8% $791 Property C 67 $382 $5.72 2.8% $204 Property D 37 $892 $24.43 2.8% $873 Property E 138 $1,946 $14.07 2.8% $503 Property F 8 $1,103 $139.19 2.8% $4,971 Property G 82 $1,532 $18.71 2.8% $668 Property H 24 $1,300 $54.54 2.8% $1,948 Property I 11 $226 $20.40 2.8% $728 Property J 80 $2,299 $28.64 2.8% $1,023

Source Three



Property A 29 $500 $17.24 5.0% $345 Property B 28 $500 $17.86 5.0% $357 Property C 24 $500 $20.83 5.0% $417 Property D 25 $500 $20.00 5.0% $400 Property E 32 $500 $15.63 5.0% $313 Property F 16 $500 $30.91 5.0% $618 Property G 8 $500 $58.84 5.0% $1,177 Property H 46 $500 $10.87 5.0% $217 Property I 21 $500 $23.81 5.0% $476 Property J 11 $500 $45.45 5.0% $909

Source: MyNewPlace client data, 2008

23


Conclusion Understanding the relative efficiency of a given set of advertising sources is critical to maximizing the effectiveness of an owner/manager’s ad spend. Using tried and true direct marketing methodologies to track and calculate costs on easily comparable metrics, such as cost per unique lead or guest card, can provide this understanding. However, the multifamily marketing professional must be careful to follow a few simple rules to ensure that the data does not become biased or misleading. This can happen either because of shortcuts (such as not de-duping to get unique leads), or because the analysis is pushed too far when accurate data is not available (such as using the cost-per-lease data from a PMS, rather than performing a name-matching exercise with guest cards). In summary, these rules are:

1. Identify Sources: Collect complete information on each source and be careful to compare like time periods.

2. Determine Common Metric: Choose a metric that can be calculated for each source accurately. Make sure you compare each source against this metric. Do not choose a metric (such as cost per lease without name matching) that pushes the envelope in terms of your ability to do the calculations quickly or accurately.

3. Benchmark Sources: Compare your sources across the same time period, including all relevant cost data for featured properties and other add-ons.

4. Allocate Spend (and Efforts): Remember – this exercise produces good relative, not absolute, measures. An advertising source will produce some prospects who do not email or phone first, so do not assume that a cost-per-lease figure is the absolute cost per lease for that source – it is likely lower than what you calculate. (Also, a short time period for gathering the lease data for a name-matching exercise can also understate the number of leases generated.) However, do use these relative measures to rank your sources for each property, and choose those that are most cost effective until you think your leasing needs are met. Of course, if a source has a very high cost per lead or cost per lease on an absolute basis, you will probably want to cut that source unless your lead needs are very acute. The more certain you are of your analysis, the closer you can draw the line in terms of an unacceptable cost.

5. Repeat: Once you have built your cost-per-unique-lead or guest-card spreadsheet, keep it updated monthly to ensure no one source suddenly starts underperforming. The more detailed cost-per-lease exercise can be done annually or semiannually to ensure that you are calibrating your leads accurately.

While at first the analysis we show may appear time-consuming and difficult, we are confident that if done properly on a property-by-property basis, most owner/managers should be able to identify 15 percent to 30 percent of their ad spend that, even on a relatively high absolute basis, is not worth the money. By systematically identifying the sources that have the lowest cost per lead/guest card (and ultimately lease) by property, owner/managers should be able to reallocate part of their savings to replace the leads lost from the more expensive sources at a fraction of the cost, thereby easily saving 10 percent to 20 percent of their overall budget. In subsequent years, by further refining the analysis, watching each source closely, and testing new possible low-cost sources, an owner/manager should be able to wring out future savings or get more leads for the same spend, thereby raising occupancy and increasing the likelihood of pushing up rents.

“Do not choose a metric (such as cost per lease without name matching) that pushes the envelope in terms of your ability to do the calculations quickly or accurately.”

“…we are confident that if done properly on a property-by-property basis, most owner/managers should be able to identify 15 percent to 30 percent of their ad spend that, even on a relatively high absolute basis, is not worth the money.”

24


Appendix A – Simple Cost per Non-duplicate (or Unique) Lead Analysis The following is a set of instructions to complete a simple cost per unique lead analysis for all of your advertising sources for one month.

For this analysis, here is what you will need from each advertising source:

1. A monthly property report, showing how many email and phone leads each property received (each ILS should provide this to you monthly, or you can download it from most of their sites – we recommend you contact your sales representative from each respective source if you need instructions on how to get this report)

2. Total monthly cost by property for each source (we strongly recommend you use the negotiated rate in your contract with each source as opposed to your internal accounting, as ledger entry dates do not always line up by property by month)

Complete the following steps for one ad source, and then repeat for each additional ad source.

Step 1: Create a table with the following columns:

1. Property Name

2. Cost

3. Email Leads

4. Phone Leads

5. Total Leads

6. Cost/Lead

7. Unique Leads

8. Cost/Unique Lead

Step 2: Copy and paste the following columns from the monthly property report into your table: (1) Property Name, (2) Email Leads, and (3) Phone Leads.

Step 3: Enter the cost for each property. This can either be provided by the advertising source for the specific month, or you can use the negotiated monthly rates.

Step 4: Calculate Total Leads by adding together Email Leads and Phone Leads for each property.

Step 5: Calculate Cost/Lead by dividing Cost by Total Leads for each property.

Step 6: Calculate number of Unique Leads. Some sources report gross leads (which include duplicate leads) while others report unique leads. For a more accurate analysis, you should estimate unique leads.

25


Rent.com and MyNewPlace both report unique leads, so for these two sources, the Unique Leads column should be identical to the Total Leads column. For most other sources, you will need to multiply Total Leads by a deduplication ratio to estimate Unique Leads.

To calculate the deduplication ratio, simply take a sample set of actual lead data (provided in your reporting from each respective source) and count the duplicate originating phone numbers and email addresses, then calculate the ratio. For example, if you had 30 leads, but there were six sets of leads from the same phone number or email address, then you actually had 24 unique, or non-duplicate leads, thus, the deduplication ratio would be 24/30, or 85%.

Generally, most of the sources other than Rent.com and MyNewPlace, which report unique (non-duplicate) leads, have deduplication ratios of between 70 and 90%, so using a ratio of 80 to 85% across the board if you are unable to calculate the ratio as described above should suffice.

Step 7: Calculate Cost/Unique Lead by dividing Cost by Unique Leads for each property.

Repeat this process for each advertising source.

26


Appendix B – Advanced Cost per Non-duplicate (or Unique) Lead Analysis for Large Portfolios

Part One: Data Collection

Step One: Pulling Online Reports The first step in doing this analysis is collecting data from each of your sources. Use their online reporting interfaces to easily pull the data you need. There will be several reports available, so look for monthly reports by property. Note that Rent.com has two separate reports for leads and leases. For this analysis, only lead data is necessary.

Step Two: Standardizing and Organizing Data Once you have collected all of this information, standardize and organize the data. This is extremely important: assuming you are analyzing five ILSs over a three month period, you now have about 15 spreadsheets, each formatted differently, some with merged columns, data split over several tabs, or cells formatted as text and unrecognizable by formulas. Organization is integral to simplifying the process and preventing errors; the time you spend now will have a big impact as you continue.

Create one spreadsheet for each ILS, taking care to name each file consistently, i.e. ILS1 Data.xls, ILS2 Data.xls, etc.

In each spreadsheet, create a tab for each month that you are analyzing, again making sure to be consistent across all worksheets. While consistency in naming is helpful for the user, it will also simplify Excel formulas when aggregating the data.

Copy and paste the information from each downloaded spreadsheet into the appropriate spreadsheet and tab. Many of the reports will include several columns of unnecessary information. For this analysis, only Property Name, (Unique) Email Leads, and (Unique) Phone Leads are needed. When pasting, make sure to look out for reports with data split across multiple tabs, merged columns, or numbers as text. For the cleanest end result, it is often best to paste values during the process. Also, remove any properties you do not want included in the analysis, such as basic listings (or listings which you have not contracted) for which there is no cost.

Step Three: Additional Information from Each ILS

Add an additional column for cost. Either have each ILS fill in the correct data or use negotiated contract rates. As mentioned earlier, having this filled in by your accounting staff can lead to erroneous data, as invoices are not always paid in the same calendar month.

Note that for certain ILSs, the notion of cost per property for a specific month may not make sense. For example, on a pay-per-lease model, it’s difficult to know the cost that would correspond to a given month’s leads because most leases occur after the month that a consumer first views a property.

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Exhibit B1: Sample completed data worksheet. Note the worksheet name and tabs.

Part Two: Aggregating the Data

Step One: Property IDs

Because property names can vary across sources, standard IDs are necessary to aggregate all of the data by property. Create a new workbook that will serve as the main workbook where you aggregate all of the data. Now, create a Property ID worksheet. This worksheet will serve as a lookup table to assign property IDs to the properties in your data workbooks.

First, list all of the spelling variations of your properties in one column. (A fast way to do this is to copy and paste the property names from all of your data workbooks into the column. Then, use the remove duplicates feature in Excel to pare down your list.) Now, assign IDs to each property name, taking care to assign the same ID to different name variations of the same property, as illustrated in the example.

Exhibit B2: Completed Property ID tab

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Exhibit B3: Updated tab in Source 1 Data workbook – now contains property IDs

Once you have created your master list, add a Property ID column to your data worksheets and assign the IDs. You can do this quickly by using Excel formulas such as VLOOKUP or a combination of INDEX and MATCH.

For example, to assign the correct property ID in cell A2, the correct formula is:

= INDEX('[Property Analysis.xlsx]Property ID'!$A:$A,MATCH(B2,'[Property Analysis.xlsx]Property ID'!$B:$B,0))

This formula matches the value in B2 to a value in column B of the Property ID worksheet in the Property Analysis workbook and returns the value’s row number. It then looks in column A for the value in the same row.

Step Two: Consolidating Into One Workbook

In a new worksheet in your main workbook, create an outline to bring all of the data together. Again, standardization is key. In the example below, there are seven columns of metrics, which are then repeated for each source/month combination:

1. Cost 2. Email Leads 3. Phone Leads 4. Total Leads 5. Cost/Lead 6. Unique Leads 7. Cost/Unique Lead

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Exhibit B4: Incomplete aggregate worksheet

The first three columns’ data can be pulled from your data worksheets; the rest are calculated. These columns repeat for each source and month.

To fill in the data, use the SUMIFS function. (This function was introduced in Excel 2007. For earlier versions of Excel, check online for alternate functions.)

For example, to calculate Property A’s cost for Source 1 in June, enter the following function:

= SUMIFS('[Source1 Data.xlsx]June'!$E:$E,'[Source1 Data.xlsx]June'!$A:$A,$A6)

This sums any cost value in column E of the July tab in the Source1 Data worksheet where the adjacent value in column A matches value A6. (The $ in front of A6 indicates an absolute reference.) For a given source and month, you should be able to copy this formula into the other columns with only minor adjustments for which column should be summed. Once you have completed one set of data, you can copy and paste the entire seven columns into the next month and find and replace the tab name.

That is, for the partially completed worksheet below, the next step is to copy and paste cell C6 through I15 into J6 through P15. Then, find and replace ‘June’ with ‘July.’ If the layout of your data worksheets was standard across all ILSs and months, you can use the same technique to fill in the remainder of cells, finding and replacing ‘Source1’ with ‘Source2,’ etc.

Exhibit B5: Partially completed aggregate worksheet

Note, while the calculated columns are fairly straightforward, unique leads can done in several ways and vary by source. For example, in summary lead reporting, both MyNewPlace and Rent.com report unique leads, whereas other sources provide gross leads. However, many sources provide details for each lead.

So, for sources that report gross numbers one can determine a deduplication rate to estimate unique leads by looking at detailed lead reports for a sample set of properties. Alternately, by looking at aggregate data across all ILSs, an overall rate can be determined to apply to all sources. This method will be less accurate and may unfairly penalize or help certain ILSs.

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Step Three: Final Adjustments

Now that you have aggregated all of the data, you can make some final adjustments to the worksheet.

1. Fill in the total and subtotal rows (row 3 and row 4). Use SUM to fill in the total row so you can see overall monthly performance by source. Use SUBTOTAL to see summations based on filters. This will allow you to see updated totals if you use filters to view only a subset of the data.

2. Hide extra columns so you see only Cost, Unique Leads, and Cost/Unique Lead. These are the metrics that you should use to compare how each of your sources performs.

3. Add auto filters – these will allow you to quickly sort and filter columns. As you filter data, the subtotal column will automatically update.

Exhibit B6: Completed aggregate worksheet

Part Three: Analysis

Now that you have created your final workbook, you can easily compare monthly ILS performance across all of your properties.

Cost-Effective Resident Acquisition · 2009. 6. 9. · 4 Cost-Effective Resident Acquisition...

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