Using Data to Align a Retail Mall with the Market
Shopping centers provide life to many communities and neighborhoods. With well curated retail stores, restaurants, services and programming, they provide places to shop, meet, entertain, interact, learn, nourish and people watch. At their best, they become the de facto town squares of their communities.
On the other hand, there are many centers that were once lively, but have lost their lustre. The traffic has thinned, tenant turnover has taken root, programming isn’t interesting and local residents no longer see the centers as relevant to their daily lives.
Some operators have chalked their challenges up to the rise of internet shopping. After all, It is convenient to shop for an item with a few taps on a phone and have it delivered in a few hours or the next day. And, yes, internet commerce has grown, but not as much as many think. As of December 2020, the U.S. Census Bureau reported that non-store retail accounted for 16.4% of retail sales in the United States. But that also means that 83.6% of retail sales or $409 billion were spent through retail outlets just in December, $460 billion when food service is included, and these are dollars spent in the middle of a pandemic-induced recession.
If more than 80% of retail dollars are still spent in-stores, but many retail shopping centers are still struggling, then there must be another explanation.
Shopping center operators are in the business of leasing space and providing customer traffic to their retailer lessees. If there’s little traffic, retail sales suffer. Declining retail sales give quality tenants reason to move on. Tenant turnover ensues. Traffic declines further, impacting rents and cash flow. It becomes a vicious cycle. At its core, this cycle is the result of a mismatch between the center’s offerings and the “wants” and needs of key segments within the center’s market area.
Benefits of a Data-Driven View of the Market
Aligning the shopping center’s tenant mix, programming and marketing with the people in the center’s service area starts with hard data. TavuraSM takes that hard data, analyzes it and packages it for center managers, brokers, retailers, marketers and bankers to make market-based decisions.
Tenant Attraction & Curation
Tenant attraction and curation is important to the success of any shopping center. The tenant mix must fit the market. Ensuring that fit starts with insight based upon good data.
As discussions begin with prospective tenants, they need to know that they can be successful in serving the shopping center’s local market. The more data-driven information they have, the more confidence they will have in entering into a long-term lease or property purchase agreement. Tenants want to have high confidence that there is a match between their offering and the center’s targeted market segments. They want to be sure that they have a quick path to profitability after investing in the lease, build-out, start-up costs and marketing.
Shortening a single retail vacancy by just one month more than offsets the cost of a typical report that covers the entire shopping center. When used effectively shopping center managers and brokers, TavuraSM reports lead to greater market fit, higher quality retailers, more retailer success, improved rents and reduced turnover.
Shopping Center Programming & Marketing
Once the tenant mix is effectively curated, center management needs to develop reasons for people in the local community to visit and shop. TavuraSM reports provide good data to get to know the local market and its market segments so that center programming and marketing can be optimized for those that live in the service area, driving traffic and building goodwill. The true profile of the community must be known if the center is to become an integral part of the community.
TavuraSM reports also provide the information needed to set the direction for effective local partnerships. Partnering with local businesses and community-based organizations is a key strategy to become an integral part of the community. Understanding the market and its segments allows managers to develop partnerships with an eye toward inclusion and impact.
Banker & Investor Confidence
Shopping centers are backed with financing from bankers and investors. In general, bankers seek to minimize the risk inherent in their financed properties. Helping bankers understand the property’s market with data-driven reports and how center management intends to serve that market may impact lender assessment of financial risk, which could result in reduced financing costs.
Investors, on the other hand, want to see maximum return on their investment. Matching the center’s offerings with the local market is necessary to improve cash flow and grow property market value.
Example: Eagle Rock Plaza
In the Los Angeles, California, community of Eagle Rock is a local shopping center known as Eagle Rock Plaza. Eagle Rock Plaza was not a TavuraSM client as of the time of this writing, but it serves as an excellent example of how a strong understanding of the people in the service area can be used to align the center’s offerings with the market.
The market analysis below is but a small portion of a much larger, in-depth report that is typical of TavuraSM’s work. The report on which this post is based contains more than 160 pages of analysis, maps, graphs and tables. TavuraSM would be happy to review the full report with qualified prospective clients.
Subject Property Description
Eagle Rock Plaza was built in the early 1970’s and retains some of the design elements of its time. It is located within the Eagle Rock community of the City of Los Angeles between the moderately sized cities of Glendale and Pasadena. It can be seen from two nearby busy freeways, CA-134 and CA-2, which have a combined average traffic count of 729,000 vehicles per day (CalTrans). The major road It fronts, Colorado Boulevard, has a traffic count of 46,000 vehicles per day (LADOT).
Two miles to the west on Colorado Boulevard are two major Glendale shopping centers, Americana at Brand and Glendale Galleria. Pasadena’s Old Pasadena shopping district is on Colorado Boulevard five miles to the east. Given this competition, there is little chance of competing on the basis of being a destination center in its own right, so this mall’s path forward must be to integrate itself into the local community.
Eagle Rock Plaza has roughly 500,000 gross leasable square feet with Target and Macy’s as anchors at each end. In the middle, current tenants include Chuck E. Cheese’s, GNC, Dollar King, Filipino-focused Seafood City Supermarket, a few fast food outlets, a couple of jewelry and beauty stores, a few clothing stores, a Tae Kwon Do studio, a fitness studio and an armed forces recruiting center. There are a number of empty storefronts as of the time of this writing.
The pictures below were taken on a Saturday afternoon in January 2021.
Understanding the Market
Improved retail attraction and local consumer marketing starts with a data-driven understanding of the people in the center’s local service area.
TavuraSM estimated a retail trade area defined by 8-, 12- and 15-minute drive times to the shopping center. For this blog post, we’ll focus on the 15-minute drive time drawing area. For those interested in the narrower drawing areas, they are examined in detail in the report on which this blog is based. Some may use distance, such as with 1-, 3- and 5-mile rings to define a retail trade area, TavuraSM believes that drive times better reflect how customers perceive the trade area.
The 15-, 12- and 8-minute drive time areas are depicted in the map below.
Using this market area, TavuraSM calculated the characteristics of the people within the area using machine learning to break the market down into distinct market segments, to detail the characteristics of each, analyzed, interpreted and mapped by our expert analysts.
The big picture is also important. TavuraSM also details, interprets and summarizes the characteristics of the overall market. The overall market review is below.
First is a review of the identified market segments, or “clusters”.
Key Insights: Market Segment Summary
TavuraSM applies machine learning techniques to analyze each neighborhood, categorizing each into distinct market segments with common characteristics.
For this service area, four market segments or “clusters” were identified:
| Population | Median HH Income | Aggregate HH Income | |
| Cluster 1: Diverse, Educated Families in Single Family Homes | 58,931 | $95,585 | $2.55 billion |
| Cluster 2: Primarily Latino, Middle Income Families | 112,238 | $57,201 | $2.73 billion |
| Cluster 3: Educated, High Income & Mostly Living in Single Family Homes | 51,188 | $109,346 | $3.11 billion |
| Cluster 4: Apartment Dwellers, Mostly Foreign Language Speakers | 138,117 | $52,211 | $3.76 billion |
These clusters lay out through the market area as depicted on the market area map, each identified by a different color.
When viewing the market segment map, note the proximity of each cluster to the subject property. Those nearby may be more disposed to shop there, assuming there is a fit between the center’s offerings and the desires of the segment. Those farther away may have nearer options available, resulting in a reduced desire to travel the extra distance. Also note features that might serve as a physical or psychological barrier to travel, such as freeways.
Also note that each of these market segments have a substantial population with money to spend. While it is often tempting to focus on the segments with the highest median household income, they may not necessarily be the most profitable path forward. In this case, each of the four segments have from $2.6 to $3.8 billion in aggregate income. By choosing wisely, focusing on segments with less competition and more unmet needs, the center can stake out a profitable and sustainable position within the community as it serves one or more segments with distinct profiles, wants and needs.
Focusing on one or two key market segments gives center management the opportunity to curate an engaging tenant mix, develop relevant programming and target market messaging. As each segment is likely to have different preferences, wants, needs and may respond to different marketing messaging, this gives center management the opportunity to tune their offerings to strongly serve the targeted market segments.
The aim is to strongly and consistently serve each targeted segment in the best way possible. With each segment in the Eagle Rock Plaza’s market area having billions of dollars in annual aggregate income, targeting just one or two market segments will likely serve management well.
The four market segments, or “clusters”, in the market area have the following profiles.
Consumer Cluster 1: Diverse, Educated Families in Single Family Homes
Consumer Cluster 1 is comprised of an educated, ethnically diverse population with strong middle class incomes, living in primarily single family homes. Nearly half of adults have at least a bachelor degree and more than two-thirds of the population is of working age. Nearly all in the cluster are English proficient.
| Cluster 1 | |
| Population | 58,931 |
| Total Households | 20,756 |
| Household Size | 2.8 |
| HH Density per Acre | 4.6 |
Household Composition
Married couple families make up 46% of households. Non-Family Households, those headed by singles or unmarried couples and not living with relatives, comprise 37% of households. Other Family Households, headed by either a single or non-married couple living with relatives account for 17% of households.
Race/Ethnicity
This cluster is ethnically diverse with no ethnic group making up a majority of the population. Latinos and whites each comprise 36% of the population. Asians account for 22%. Looking more closely at ancestry data, 23% report Mexican ancestry and 13% Filipino ancestry.
Language at Home
English proficiency is nearly universal at 92% of households, though it is the only language spoken in just 48% of households. Other languages spoken at home include Spanish at 27%, Asian/Pacific Islander languages at 18% and Indo-European languages at 6%.
Education & Income
Median household income is $95,585, the second highest among the clusters. This is consistent with the group’s high education levels with 49% of people 25+ holding at least a bachelor degree.
| Cluster 1 | |
| High School Diploma or Less | 24% |
| GED to Associate | 27% |
| College Degree | 49% |
Aggregate Household Income for this segment, a measure of cluster spending power, is a strong $2.55 billion, even with this cluster’s relatively smaller population among the clusters. Aggregate Household Income per Acre, a measure of spending power density, is also a strong $562,602, a result of the combination of strong median household incomes and housing density.
| Cluster 1 | |
| Median Household Income | $95,585 |
| Aggregate Household Income | $2.55 billion |
| Aggregate Household Income per Acre | $562,602 |
Top Occupations & Employer Industries
The top occupations and employer industries reflect the relatively high education and income levels within the cluster. The top six occupation groupings account for 57% of the working population.
| Cluster 1 | |
| Arts, Design, Entertainment, Sports, Media | 14.0% |
| Management Occupations | 12.3% |
| Office & Administrative Support | 9.8% |
| Sales & Related | 7.6% |
| Business & Financial Operations | 7.1% |
| Education, Training & Library | 6.6% |
The top six employer industries account for 63% of the working population.
| Cluster 1 | |
| Health Care & Social Assistance | 14.3% |
| Professional, Scientific & Technical Services | 12.1% |
| Information | 10.0% |
| Educational Services | 10.0% |
| Retail Trade | 8.6% |
| Accommodation & Food Services | 7.6% |
Housing
Seventy-eight percent of households live in single family homes with much of the balance living in smaller multi-family complexes. Household density is 4.6 households per acre, typical of smaller lot single family housing communities. Fifty-eight percent of households live in owner occupied housing and 42% live in rented housing. More than half of the housing stock was built before 1950.
| Cluster 1 | |
| Owner Occupied | 58% |
| Renter Occupied | 42% |
| Cluster 1 | |
| Single Family Residence | 78% |
| 2-4 Unit Multifamily | 11% |
| 5-19 Unit Multifamily | 7% |
| 20+ Unit Multifamily | 4% |
| Mobile Home | 0% |
| Boat, RV, Van, Etc. | 0% |
Consumer Cluster 2: Primarily Latino, Middle Income Families
Consumer Cluster 2 is middle class and mostly comprised of Latino families, with an average household size of 3.2 members. English proficiency is nearly universal. The population is middle class. Education levels are slightly lower than average with workers in a mix of white and blue collar jobs. Over half of households live in single family homes, almost a third in smaller multifamily and the remainder in larger multifamily complexes.
| Cluster 2 | |
| Population | 112,238 |
| Total Households | 35,662 |
| Household Size | 3.2 |
| HH Density per Acre | 5.9 |
Household Composition
Married couples head 40% of households in this cluster. Non-family households in which household members are either single or not related by marriage or blood comprise 35% of households. Other Family Households, headed by either a single or non-married couple living with related family members, comprise 25% of households.
Race/Ethnicity
The majority of the population in this cluster is Latino, comprising 64% of the population, followed by whites at 17% and Asians 14%. Looking more closely, 47% report Mexican ancestry, 8% Filipino and 7% Salvadoran.
Language at Home
Eighty-six percent of households are English proficient. Spanish is spoken in 52% of households. English is the only language in 32%. Asian/Pacific Islander languages in are spoken in 13% and Indo-European in 3%.
Education & Income
Median household income is $57,201. This is consistent with this cluster’s modest education levels with 28% of people 25+ holding a bachelor degree or higher.
| Cluster 2 | |
| High School Diploma or Less | 45% |
| GED to Associate | 27% |
| College Degree | 28% |
Aggregate Household Income for this segment, a measure of cluster spending power, is a strong $2.7 billion. Aggregate Household Income per Acre, a measure of spending power density, is $450,077 per acre, largely due to this cluster’s population size and household density levels.
| Cluster 2 | |
| Median Household Income | $57,201 |
| Aggregate Household Income | $2.73 billion |
| Aggregate Household Income per Acre | $450,077 |
Top Occupations & Employer Industries
The top six occupations account for 50% of the working age population.
| Cluster 2 | |
| Office & Administrative Support | 11.6% |
| Sales & Related | 10.2% |
| Management Occupations | 7.5% |
| Food Preparation & Serving Related | 7.3% |
| Arts, Design, Entertainment, Sports, Media | 7.1% |
| Building Grounds, Cleaning & Maintenance | 6.4% |
Top employer industries employ 56% of the working population.
| Cluster 2 | |
| Health Care & Social Assistance | 12.7% |
| Retail Trade | 11.3% |
| Accommodation & Food Services | 10.3% |
| Manufacturing | 7.7% |
| Educational Services | 7.4% |
| Other Services Except Public Administration | 6.7% |
Housing
Household density is 5.9 households per acre, which is reflective of the mix of 55% of households living in single family housing and 45% in multifamily housing. Sixty-five percent of households rent their dwellings while 35% own.
| Cluster 2 | |
| Owner Occupied | 35% |
| Renter Occupied | 65% |
| Cluster 2 | |
| Single Family Residence | 55% |
| 2-4 Unit Multifamily | 13% |
| 5-19 Unit Multifamily | 18% |
| 20+ Unit Multifamily | 14% |
| Mobile Home | 0% |
| Boat, RV, Van, Etc. | 0% |
Consumer Cluster 3: Educated, High Income & Mostly Living in Single Family Homes
Cluster 3 is comprised largely of educated, high-income small families. The majority of the population is white with Asians and Latinos together making up almost one-third of the population. English proficiency is nearly universal, though non-English languages are the primary languages spoken in 41% of households. More than half hold jobs in white-collar occupations reflective of the education levels of the cluster.
| Cluster 3 | |
| Population | 51,188 |
| Total Households | 20,787 |
| Household Size | 2.5 |
| HH Density per Acre | 2.4 |
Household Composition
Married couples head up 49% of households. Non-Family Households, those headed by a single or unmarried couple and not living with relatives make up 41%. Other Family Households, headed by a single individual or unmarried couple living with related family members, account for the remaining 11%.
Race/Ethnicity
Whites comprise 61% of the population, followed by Asians at 17% and Latinos at 15%. Looking more closely, 13% report Armenian descent, 9% Mexican descent, 9% German descent and 8% Irish descent.
Language at Home
The vast majority of households, 93%, are English proficient, though English is the only language spoken in just 59% of households. At least 34% speak non-English languages at home, but are also English proficient. Indo-European languages are spoken in 15% of households, Spanish in 13% and Asian/Pacific languages in 12%.
Education & Income
Median household income for this cluster is the highest among the clusters at $109,346. This is consistent with the group’s high education levels in which 61% of people 25+ hold a bachelor degree or higher.
| Cluster 3 | |
| High School Diploma or Less | 16% |
| GED to Associate | 24% |
| College Degree | 61% |
Aggregate Household Income for this segment, a measure of spending power, is substantial at $3.11 billion. Aggregate Household Income per Acre, a measure of spending power density is $356,393.
| Cluster 3 | |
| Median Household Income | $109,346 |
| Aggregate Household Income | $3.11 billion |
| Aggregate Household Income per Acre | $356,393 |
Occupations & Employer Industries
The top occupations and employer industries are white-collar and typical of what would be found in communities with high education levels. The top six occupations account for 63% of the working population.
| Cluster 3 | |
| Management Occupations | 16.0% |
| Arts, Design, Entertainment, Sports, Media | 13.2% |
| Sales & Related | 9.7% |
| Office & Administrative Support | 9.6% |
| Business & Financial Operations | 7.4% |
| Education, Training & Library | 7.3% |
The top employer industries account for a similar 61% of workers.
| Cluster 3 | |
| Professional, Scientific & Technical Services | 14.6% |
| Health Care & Social Assistance | 13.0% |
| Information | 10.5% |
| Educational Services | 10.2% |
| Retail Trade | 6.6% |
| Arts, Entertainment & Recreation | 6.6% |
Housing
Fifty-nine percent of households live in single family homes and 41% live in multifamily complexes. Homeowners comprise 54% of households while 46% rent their dwelling. Household density is 2.4 households per acre, a typical density for less dense suburban single family communities.
| Cluster 3 | |
| Owner Occupied | 54% |
| Renter Occupied | 46% |
| Cluster 3 | |
| Single Family Residence | 59% |
| 2-4 Unit Multifamily | 10% |
| 5-19 Unit Multifamily | 13% |
| 20+ Unit Multifamily | 19% |
| Mobile Home | 0% |
| Boat, RV, Van, Etc. | 0% |
Consumer Cluster 4: Apartment Dwellers, Mostly Foreign Language Speakers
Consumer Cluster 4 has the largest population among the clusters. The population is middle class with a slightly higher than average education level. Whites make up a majority of the population with a large portion reporting Armenian ancestry. Together, Latinos and Asians make up much of the remaining population. Seventy percent of households are English proficient with English the primary language spoken in just one-quarter of households. Indo-European languages are spoken in nearly half of households. Most households rent units in multifamily housing.
| Cluster 4 | |
| Population | 138,117 |
| Total Households | 52,815 |
| Household Size | 2.6 |
| HH Density per Acre | 9.7 |
Household Composition
The largest portion of households, 44%, are Married family households. Non-Family Households in which household members are either single or not related by marriage or blood make up a slightly smaller portion at 36% of households. Other Family Households, headed by either a single or non-married couple living with related family members, comprise 20% of households.
Race/Ethnicity
The people in this cluster are somewhat diverse with 40% of the population from non-white minority groups. Whites make up 60% of the population, 21% Latino and 14% Asian. Looking more closely, 39% report Armenian descent, 13% Mexican descent and 8% Filipino descent.
Language at Home
Seventy percent of households are English proficient, however, just 27% speak only English in the home. Indo-European languages are spoken in 44% of households, Spanish in 16% and Asian/Pacific Islander in 11% of homes.
Education & Income
Median household income is $52,211. Thirty-five percent of people 25+ hold at least a bachelor degree.
| Cluster 4 | |
| High School Diploma or Less | 37% |
| GED to Associate | 28% |
| College Degree | 35% |
Aggregate Household Income for this segment, a measure of spending power, is highest among the clusters with a strong $3.76 billion. Median Household Income per Acre, a measure of spending power density, is $687,996 per acre.
| Cluster 4 | |
| Median Household Income | $52,211 |
| Aggregate Household Income | $3.76 billion |
| Aggregate Household Income per Acre | $687,996 |
Occupations & Employer Industries
The top six occupations account for 50% of the 15+ working population.
| Cluster 4 | |
| Office & Administrative Support | 13.2% |
| Sales & Related | 10.4% |
| Management Occupations | 8.7% |
| Arts, Design, Entertainment, Sports, Media | 6.5% |
| Healthcare Support | 5.9% |
| Business & Financial Operations | 5.4% |
The top employer industries employ 58% of workers.
| Cluster 4 | |
| Health Care & Social Assistance | 17.3% |
| Retail Trade | 10.8% |
| Professional, Scientific & Technical Services | 9.8% |
| Educational Services | 6.9% |
| Manufacturing | 6.7% |
| Other Services Except Public Administration | 6.6% |
Housing
Household size is 2.6 people. Housing density is the most compact in this cluster with 9.7 households per acre, which is reflective of the 81% of households that live in multifamily housing, primarily in complexes of 2-19 units. Eighty-two percent of households rent their homes while 18% own.
| Cluster 4 | |
| Owner Occupied | 18% |
| Renter Occupied | 82% |
| Cluster 4 | |
| Single Family Residence | 19% |
| 2-4 Unit Multifamily | 12% |
| 5-19 Unit Multifamily | 38% |
| 20+ Unit Multifamily | 31% |
| Mobile Home | 0% |
| Boat, RV, Van, Etc. | 0% |
Key Insights: Total Service Area
While market segments provide great insight into the unique population groups within the service area, it also helps to understand the profile of the overall service area. It may be less useful for key marketing decisions, but it will inform an understanding of the environment within which each of the market segments coexist. Below is a depiction of the service area with the number of people residing within each neighborhood. Darker areas have more population, lighter areas less population. Where are the higher population areas within proximity of the subject property? Cross this with the map of the market segments to gain a better understanding of market opportunities. Within the actual report, there are maps, tables and graphs along many metrics to provide an even more insight.
High Population in Service Area
The population within the service area is substantial. Within a 15-minute drive of the subject property, there are 360,474 people in 130,021 households. Within a 12-minute drive time, there are 242,142 people, nearly a quarter million, in 86,593 households. Even within the smallest service area, an 8-minute drive time, there are 115,276 people in 42,026 households.
Overall household density is 5.2 households per acre. However, localized density can vary greatly with some neighborhoods dominated by single family residences and others by multi-family complexes of varying sizes.
| 15 Minutes | |
| Population | 360,474 |
| Household Total | 130,021 |
| Household Density per Acre | 5.2 |
| Household Size | 2.8 |
Slightly Higher Than Average Education & Income
The population within the market area has a slightly higher than average education level. Across the service area, 39% of 25+ adults hold a bachelor degree or higher.
Median household income for the service area is $69,638. Aggregate Household Income is a measure of market area consumer spending power. It is the total of household incomes for the market area. With Aggregate Household Income of $12.2 billion per year, income available to support consumer spending is substantial.
Aggregate Household Income per Acre is a measure of spending power density. The combination of household density and household incomes result in Aggregate Household Income per Acre measures from $490,162 for the 15-minute market area to $541,267 per acre for the 8-minute service area.
| 15 Minutes | |
| High School Diploma or Less | 34% |
| GED to Associates | 27% |
| College Degree | 39% |
| 15 Minutes | |
| Median HH Income | $69,638 |
| Aggregate HH Income | $12.1 billion |
| Aggregate HH Income per Acre | $490,162 |
Mostly Working Age
Population age distribution is concentrated among the adult working years with 67% of the population aged 18-64. The remaining 33% is roughly evenly distributed between children and seniors, as is common in established urban/suburban areas.
| 15 Minutes | |
| 0-17yrs | 18% |
| 18-39yrs | 34% |
| 40-64yrs | 33% |
| 65+yrs | 15% |
Household Composition Mostly Married & Non-Family
The largest group of households across the three market areas are those led by married couples, comprising 44% of households in the wider 15-minute market area. Non-Family Households, those headed by unrelated singles or couples who are not living with other family members, including couples living together or non-couples sharing homes, make up 37% of households. Other Family Households include those headed by a single or non-married couple who are living with relatives, make up 19% of households.
| 15 Minutes | |
| Married Couple HH | 44% |
| Other Family HH | 19% |
| Non-Family HH | 37% |
Ethnic Make-up & Language at Home
Race & Ethnicity
The market area ethnic make-up is diverse, with no ethnic group comprising more than half of the market area population and non-white ethnic minorities making up 57% of the 15-minute drive time market area. Whites comprise 43% of the population, Latinos 36% and Asians 16%. Looking more closely, 25% report Mexican ancestry, 17% Armenian ancestry and 8% Filipino ancestry.
| 15 Minutes | |
| White | 43% |
| Latino | 36% |
| Asian | 16% |
| Two or More Races | 3% |
| African American | 2% |
| Pacific Islander | 0% |
| American Indian | 0% |
| Other | 0% |
Language Spoken at Home
A household’s language spoken at home may or may not be reflective of the language by which consumers expect to receive marketing messages or prefer to conduct business. That said, 83% of households are English proficient though just 37% speak only English in the home. Spanish is spoken in 27% of households, Indo-European languages in 23% and Asian/Pacific Islander languages in 13% of households.
| 15 Minutes | |
| English Only | 37% |
| Spanish Speaking, Limited English | 5% |
| Spanish Speaking, English Proficient | 22% |
| Indo European, Limited English | 10% |
| Indo European, English Proficient | 13% |
| Asian/Pacific Islander, Limited English | 3% |
| Asian/Pacific Islander, English Proficient | 10% |
| Other Languages, Limited English | 0% |
| Other Languages, English Proficient | 1% |
Occupations & Industries of Employment
Local occupations and employers tend to skew toward those employing skilled and white-collar workers. The top six occupations account for 52% of employed workers.
Occupations
| 15+ Working Population | |
| Office & Administrative Support | 11.6% |
| Management Occupations | 10.0% |
| Sales & Related | 9.7% |
| Arts, Design, Entertainment, Sports, Media | 9.0% |
| Food Preparation & Serving Related | 5.7% |
| Business & Financial Operations | 5.6% |
Employer Industries
The top six employer industries account for a similar 57%.
| 15+ Working Population | |
| Health Care & Social Assistance | 14.7% |
| Retail Trade | 10.0% |
| Professional, Scientific & Technical Services | 9.8% |
| Educational Services | 8.1% |
| Accommodation & Food Services | 7.5% |
| Information | 7.3% |
Housing is Mixed, Older & Mostly Rented
Housing in the wider market area is divided roughly evenly between multifamily and single family homes. In the 15-minute market area, 55% of households reside in multifamily housing, such as apartments and condominiums, with 35% in complexes of 5-49 units, 9% in large complexes of 50+ units and the balance in smaller complexes of 2-4 units. Forty-five percent of households live in single family homes.
Consistent with the high proportion of multifamily housing, approximately two-thirds of housing is renter occupied. The balance is owner occupied.
Housing age skews toward older structures. More than half of housing was built before 1960, 40% of it before 1950. Only 12% was built in 1990 or later.
| 15 Minutes | |
| Single Family | 45% |
| Duplex | 4% |
| 3-4 Units | 8% |
| 5-9 Units | 12% |
| 10-19 Units | 12% |
| 20-49 Units | 11% |
| 50+ Units | 9% |
| Mobile Home | 0% |
| Boat, RV, Van, Etc. | 0% |
| 15 Minutes | |
| Owner Occupied | 35% |
| Renter Occupied | 65% |
| 15 Minutes | |
| Built 2014 or later | 1% |
| Built 2010 to 2013 | 1% |
| Built 2000 to 2009 | 4% |
| Built 1990-1999 | 5% |
| Built 1980-1989 | 10% |
| Built 1970-1979 | 12% |
| Built 1960-1969 | 14% |
| Built 1950-1959 | 12% |
| Built 1940-1949 | 10% |
| Built 1939 or earlier | 30% |
This is Great, But How Do I Use It?
Eagle Rock Plaza is a shopping center that, as of this writing, has its challenges. With its current tenant mix, apparent Asian focus and vacant storefronts, clearly something is missing. Given the analysis above, the mismatch with the market is evident. This is where data-driven analysis provided by TavuraSM comes in.
Ultimately, it is up to shopping center owners, management and real estate representatives to decide on which target markets to serve, curate the tenant mix to serve that target and develop marketing and partnerships to attract the traffic. Every management group has their preference and point of view as to how to proceed, but they matter little if the leasable space cannot be filled and local residents do not visit, linger and spend.
Pick the Segments to Target
While a shopping center is real estate-based, the operators and brokers are really in the business of marketing. They market their space and traffic to retailers. They market the center and all that it offers to consumers in the local community. Few marketers are successful in marketing to everyone. The great ones pick their market segments carefully and serve them very well.
As a reminder of the segments broken out above, here are the market segment map and 15-minute market area summary table from the “Key Insights: Market Segment Summary” section.
| Population | Median HH Income | Aggregate HH Income | |
| Cluster 1: Diverse, Educated Families in Single Family Homes | 58,931 | $95,585 | $2.55 billion |
| Cluster 2: Primarily Latino, Middle Income Families | 112,238 | $57,201 | $2.73 billion |
| Cluster 3: Educated, High Income & Mostly Living in Single Family Homes | 51,188 | $109,346 | $3.11 billion |
| Cluster 4: Apartment Dwellers, Mostly Foreign Language Speakers | 138,117 | $52,211 | $3.76 billion |
First of all, each individual segment has significant spending power, ranging from $2.6 to $3.8 billion in annual aggregate household income. This means that any individual segment or combination of segments will likely sustain a well-positioned shopping center.
In determining the segments to target, the key question becomes which ones can the center serve well while minimizing competition and recognizing the impact of perceived impediments in the minds of customers.
Often, a good place to start is to set aside segments that may be difficult to serve. Cluster 3 (light green) may have the highest median household income, but it is also the segment that has the most competition for their attention and spending, particularly from the nearby Glendale Galleria, Americana at Brand and Old Pasadena shopping areas. Cluster 4 (dark green) has the highest aggregate household income, but the perceived physical barrier of the CA-2 freeway between the center and where that segment resides may pose a challenge.
The clusters that remain, Cluster 1 (light blue) and Cluster 2 (cobalt blue), present a clear opportunity. Together they have a population of 171,169 in 56,418 households and an aggregate household income of $5.3 billion. They are located to the east and south of the nearby freeways, so physical barriers are not an issue.
The combined make-up of Clusters 1 and 2 is 54% Latino, 24% white and 17% Asian. Looking more deeply within the Latino group, 39% identify with Mexican, 6% Salvadoran and 2% Guatemalan ancestry. Within the Asian group, 9% identify with Filipino and 4% identify with Chinese ancestry.
With regard to languages spoken, 88% of households are English proficient, but only 38% speak English at home. Spanish is spoken in 43% of homes, Asian/Pacific languages in 15% and Indo-European languages in 4%. Approximately 80% of each foreign language group is English proficient.
While there are differences in education and income levels between the two clusters, the overall, median household income is $71,322 and 36% of adults 25+ hold at least a bachelor degree. The top occupations skew toward white collar and creative class jobs, many of which require a college education. Top employer industries skew toward those requiring education or specialized training, including health care, professional/scientific/technical services, education and information.
They live in older housing, indicating established neighborhoods. Sixty-three percent of households live in single family homes. Of the 36% that live in multifamily housing, 27% live in smaller complexes of 2-19 units and 9% live in larger complexes of 20 or more units.
Insight To Action
This profile, while brief, paints a clear picture. It shows that Clusters 1 and 2 combined are middle class, lean Latino, and are multi-cultural, multi-lingual and English proficient. The population is a little bit better educated than the rest of Los Angeles County and a large portion of the working population work white collar or professional jobs.
With this fact-based profile, management can recruit strong tenants that match the market. They can develop events that strongly link the center to the community; events with impact and relevance to the targeted segments, building traffic and growing retail sales. Marketing messaging and placement can be honed to maximize impact, top of mind and daily visits.
Shopping center success and profitability starts with knowing the market, its size, geographic coverage, and the characteristics of the people management is seeking to attract. TavuraSM provides analysis and reports to make that possible.
Success Requires Good Data
TavuraSM analysis is insightful, full of data and valuable to marketers, commercial real estate brokers and retail offerings to use in matching their offerings with their local markets. All good marketing starts with good facts, and TavuraSM provides them.
An analysis such as the one above, can become the fact-based basis for shopping centers to match their retailers and marketing efforts with their local markets. Real estate brokers can use them to attract and sign profitable property leases with strong retailers, rooted in better market information, thereby improving property demand and negotiating position. Retail and restaurant chains can use them to analyze and align market opportunities for any current or prospective establishment, or even to search for regions with profitable opportunities. Financial institutions can use TavuraSM reports to assess property-market fit to make decisions related to lending or investing in retail property transactions.
TavuraSM reports and analyses can be used across a range of applications where insight into customers based upon location matters. Standardized and custom reports provide the insightful analysis to support a range of industries nationwide. Ultimately, TavuraSM’s goal is to help clients make money from its work.
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