Overview
Client: Boutique luxury property agent
Business structure: Small business
Lifecycle stage: Shakeout
Campaign Budget: $6000
Planning Duration: 1 week
This case study outlines the preparation of a marketing plan for a boutique luxury property agent based in Sydney’s eastern suburbs. The agent had its current website built and marketing program established over four years ago, and is looking to refresh its digital presence with a more modern image while increasing its reach to take advantage of the release of new high-end apartment buildings and renovations in metropolitan Sydney by leveraging its longstanding reputation for achieving the best price for the seller within a reasonable turnover time.
Analysis
79% of residents prefer to tour properties, renew leases, request maintenance, and interact with management using self-service.
Source: McKinsey & Company, 2024.
Market
“Memorable brand experiences, combined with the right data and technology to personalise touchpoints—including generative AI (gen AI) and digital marketing platforms—can stimulate willingness to choose a given property, higher renewal rates, and lifetime loyalty.” - McKinsey & Company, 2024.
Global business management consultancy, McKinsey & Company, has released three key articles since December 2023 that provide insight into real estate marketing today (McKinsey & Company 2023 and 2024, and Wolkomir, 2024). McKinsey & Company (2023) presents seven steps a real estate agency can take to use generative AI to create a competitive advantage, within four categories: improving customer engagement through conversational chatbots to streamline customer service, tools that generate new creative content, prompting for concise insights from unstructured data, big data, and conversations, and producing coding solutions.
Relevantly, in regards to the communication aspects of customer experience, using copilot technology in interactions between the property agent and prospective or existing clients, whether in rentals or sales, can enhance the process and improve outcomes in areas like negotiations, while learning from client communications, and providing coaching to the team to increase quality and reduce risk.
For the physical aspects in areas like property inspections and tours, prospective buyers or renters could not only take a virtual reality tour, but be able to add images of their own furniture and furnishings into the video of the empty property in order to
personalise the virtual environment and gain a more accurate preview of life after moving in, enabling a faster decision. They may instead or in addition choose to add images of furniture that they are thinking of buying from an ecommerce store, and the purchase and delivery of the furniture be arranged to coincide with the move-in.
McKinsey & Company (2024) expands this idea further to describe “tech-enabled brand, CX, and loyalty” (p.1), where a higher level of customer experience (CX) can be provided through powerful brand interactions, thoughtful touchpoints along the customer journey, and reducing operational costs. Examples are provided from hospitality and travel how different companies have deployed gen AI and other AI automation technologies to improve CX, noting that the real estate industry can equally interpret and apply these insights to their own use cases.
Wolkomir (2024) discusses how branding of residential property can enhance customer experience and loyalty, and increase the likelihood of a buyer or renter choosing to purchase or lease a property, and that this follows the trend of offering residents and investors a hotel experience. For example, branded gyms, restaurants or cafes, furnishings, retail, or architecture can enhance the attractiveness of the property in this way. This insight can be used by an agent in not only how they market different properties; also the networks and partnerships they establish with others.
Regardless of how the property agent considers these insights provided through McKinsey & Company (2023 and 2024, and Wolkomir, 2024), returning to McKinsey & Company (2023), the key step is to adopt a data focus, because it is those with the data that will be able to make the most of gen AI capabilities in order to generate insights, tools, and strategies in order to remain competitive. Towards this end, the marketing plan prepared for the property agent in this case study aims to instill the beginnings of this through the marketing function by enabling data visibility, collection, and preparation for its use in advanced analytics when the time comes.
Target Audience
The target market for the property agent are high-net-worth individuals aged 35-65 years old with executive-level or above occupations in finance, management, medicine, and similar industries, primarily located in Sydney and other Australian capital cities, with possible interest from overseas buyers. This consumer group tends to value quality, exclusivity, and high-convenience living, with an interest in lifestyle amenities, such as proximity to cultural hubs, fine dining, and recreational activities. They tend to be environmentally conscious, seeking sustainable and smart home features. On a day-to-day basis these consumers typically engage with luxury brands on social media, prefer personalised experiences with exceptional customer service, and are likely to use digital platforms for property research and virtual tours.
SWOT
Performance Reporting
Tools
Google Analytics to track website traffic, user behavior, and conversion rates, and to leverage AI-driven insights for predictive analytics.
Google Data Studio to create customisable dashboards and reports that visualise data from multiple sources, including Google Analytics and CRMs.
Hubspot for tracking email marketing performance, lead generation, and customer interactions, and AI features can help optimise campaigns.
SEMrush or Ahrefs to monitor SEO performance, keyword rankings, and backlink profiles, with AI tools to analyse trends and suggest optimisations.
Buffer to track engagement metrics, audience growth, and content performance across social media platforms.
CRM to analyse customer interactions, sales performance, and lead nurturing processes.
Reporting
Comprehensive monthly reports summarising key metrics across all channels (website, email, social media, SEO), including insights on trends, successes, and areas for improvement.
Shorter, higher-level weekly dashboards focusing on immediate performance metrics, such as website traffic, recent email campaign performance, and social media engagement.
Quarterly, in-depth analysis of overall marketing performance, assessing campaign effectiveness, ROI, and strategic adjustments for upcoming quarters.
Dashboard Design
Summary & References
This case study discussed the preparation of a marketing plan for a boutique luxury property agent located in Sydney’s eastern suburbs. With “mountains” (McKinsey & Company, 2023, p.1) of data at hand, real estate agents are in prime position to adopt AI and gen AI, and to participate in AI technology developments over the next decades. With marketing one of the most data-focused functions in a business, it could be a great place to start for those who have been waiting on the sidelines, and for those who have eagerly stepped into the less known it could be the domain they experience the earliest and most powerful benefits.
REFERENCES
McKinsey & Company (2023). McKinsey Quarterly: Generative AI can change real estate, but the industry must change to reap the benefits.
McKinsey & Company (2024). The new real estate investment edge: Tech-enabled brand, CX, and loyalty.
Wolkomir, A. (2024). Re:think - The power of branding and CX in residential real estate.
