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What is a review mining in real estate?
Review mining in real estate is the process of systematically extracting, categorising, and analysing user-generated reviews from platforms like Google, Housing.com, MagicBricks, or 99acres to identify recurring themes, issues, and strengths about a property, developer, or location. It goes deeper than sentiment analysis by identifying specific topics mentioned in reviews.
How Review Mining Works
- Reviews are scraped or collected from multiple online platforms.
- NLP techniques extract entities and topics (e.g., 'amenities', 'builder quality', 'location', 'delays').
- Each review is tagged with relevant themes and a sentiment label.
- Frequency and sentiment of each topic are aggregated.
- Reports show what buyers love or hate most — and why.
Insights Extracted from Real Estate Reviews
- Construction quality complaints (leakage, poor finishing).
- Delay in possession a major negative theme in Indian residential real estate.
- Praise for location, connectivity, or green spaces.
- Concerns about maintenance charges or society management.
- Appreciation for responsive customer service.
Review mining transforms raw user feedback into structured, actionable intelligence. For real estate developers and platforms, it is an invaluable tool for improving product quality, customer experience, and competitive positioning.
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Technology and Innovation
Evolution of Customer Relationship Management tools
‘‘The purpose of a business is to create and keep a customer’’, Peter Drucker, a famous writer, and management consultant said prolifically. The realm of CRM scope covers customer discovery, interactions, service, care, retention, and loyalty. The term Customer Relationship Management (CRM) was coined in the early 1970s when management at business units realized it would be better to be customer emphatic rather than product emphatic. Customer relationship management tools has evolved gradually from Rolodex’s of 1950s to Generative AI in 2020. What started as a record-keeping tool gradually evolved into digital documentation, sales automation, enterprise resource planning, social marketing, to the present age hyper personalised automated communication form. 1956 - First CRM Gadget - Rolodex In 1956s, Danish engineer Hildaur Neilsen, chief engineer of Zephyr American invented Rolodex, a card index system used to store customer contact information. It was a desk gadget that stacked and stored business cards and index cards that people could spin and flip through. Digital Rolodex, Tele sales and advent of computers The 1980s saw an evolution in sales, marketing and customer retention tactics with the advent of digitisation. Tools such as direct mail, brochures, and product catalogues being sent to a database of customers to get them to buy something were prevalently used in the 1980s. Database marketing and digital Rolodex came to the fore. The late 1980s saw the advent of telesales for customer communication. Computers were also accessible for enterprises and became a means of storing information about customers. In 1987, the software programme ACT (Activity Control Technology) was created by Mike Sullivan and Mitch Muhney, officially known as the first CRM software. This was essentially a digital Rolodex that allowed storage and management of the entire customer lifecycle information on the software. With its usage of Customer Relationship Management software, Act! demonstrated the advantages of scalable software that utilized consumer information to help a firm better manage its connections. 1990 - Sales Automation and progression into CRM systems By 1990s, one saw a progression of database management into customer lifecycle management and sales force workflow automation. Tools like enterprise resource planning, and marketing were added to the software’s contact management functions. This was the emergence first CRM systems. Tom Siebel, founder of Sieble Systems, coined the term CRM (Customer Relationship Software) for the first time. The post-introduction of the same CRM took off exponentially, with other companies also providing CRM solutions. Siebel Systems was later acquired by Oracle for over USD 5 billion in 2005. Late 1900s - First Mobile CRM, SaaS business model and Salesforce Inc. Post invention of PDA (Personal Digital Assistant) devices, tasks, emails, and calendar management became mobile. It allowed sales individuals to access customer data from central databases on the go, which proved to be a game changer as one didn’t have to be on the desk to work out these tasks. Salesforce.com was launched in 1999 and offered a new business model, offering software services as subscriptions (SaaS), wherein the upfront implementation cost, effort, and maintenance would be taken care of by Salesforce. 2000 - Cloud based CRM, Open-Source CRM and Social CRM In 2007, internet boom and cloud storage led to the advent and proliferation of Cloud-based CRM. With the increased internet adoption, Salesforce’s subscription model became popular as it could be scaled up very quickly. Open-source software also came to the fore, with the most prominent one being Sugar CRM, invented by computer scientists and ex-IBM and Hewlett-Packard employees Clint Oram, John Roberts, and Jacob Taylor. With the increased proliferation, and exponential growth of social media platforms, CRMs were combined with social media tools to offer SCRM. 2010 - Artificial Intelligence and CRM Artificial intelligence (AI) has changed the CRM space substantially with automation and intelligence. AI can be used for lead scoring, identifying customer needs, and providing recommendations. With enormous data being generated across every consumer by way of their digital footprint, CRM with AI and data analytics makes it simple to extrapolate consumer behaviour and requirements in real-time. 2020 and Now - Generative AI Generative AI is a subset of AI but unique in its ability to learn from underlying patterns to create new data that mirrors the training data set. The power of creation has a multifold impact across industries, and consumer communication is only to benefit from this capability. Managing customer interactions with Gen AI has the potential to enable a better connection between brands and customers. This however requires creative ability to engage customers and ability to execute to deliver better performance results and employee experiences. A combination of Gen AI and CRM can impact functional domains of marketing, sales, commerce, service and customer success. The true potential of Gen AI can be unlocked best when used in combination with predictive AI, voice to text, experience management and workflow optimisation. The CRM journey has reached an interesting point with AI, and the future looks promising for this space. The Total Addressable Market is set to grow to USD 290 billion by 2026. Salesforce Inc, an early mover, and a global market leader grew 10x in revenue in a decade. In 2013, its revenue stood at USD 3.1 billion which stands at USD 34 billion in FY 2022. CRM, which started as a simple Rolodex, has evolved into a complex system laced with artificial intelligence that helps organisations manage customer data and engage them with it in a self-assisted automated format, bringing huge implications for cost, efficiency, and the experience of consumer communication. As we advance further into the coming decades, CRM software systems will become more intelligent, integrated and intuitive with powerful AI capabilities, greater emphasis on self-service, enhanced experience for customers, hyper-personalisation, integrated API networks and ecosystems, and a single source of truth for businesses. Peter Drucker will be smiling in his grave looking at the advancement in this space.
PropTech Pulse Editorial
12th April 2024
Technology and Innovation
Gen AI and the Changing Landscape of CRM
‘‘The purpose of a business is to create and keep a customer’’, Peter Drucker, a famous writer, and management consultant. Every business, lives, profits and grows with this mantra. Business that succeeded across all the previous industrial revolutions including mechanisation, electrification, automated production, and computation have one common trait. Each of this business not only changed consumer lives but also the experience of interaction with the business and utilisation of its product or service. So, what changes today, in the 4th industrial revolution that was set off by the advances in computing and information and communication technology and is built on 4IRs. Firstly, connectivity, data and computational power, second - analytics and intelligence, third human–machine interaction and fourth - advanced engineering. These form the 4 pillars of Industry 4.0. Technology, is only half of what businesses have to adopt and change. Two additional major factors that change the business environment are, customer demographics and behaviours and introduction of new business models. Marketing and sales strategies have fundamentally aligned on to the consumer behaviour of wanting goods and services on demand and scarcity of time and attention span. Information and content is delivered and consumed on mobile phones, with GenZ and Millennial tech savvy consumers attending only to content that they find targeted, relevant and authentic. Customers of today, in addition to goods and service also want convenience, self-service and personalisation. Some common traits of the contemporary customer are, that they are well informed and self-educated, self-directed, fast paced, picky, contradictory, always connected, volatile and tech innate. Beyond product and service innovation, new business models like freemium, pay-per-use, low monthly subscriptions are engaging consumers continuously to ensure sustainable revenue streams, reaching profitability and turning recent adopters into loyal customers. Thus, ensuring long lasting relationships with customers have become a key aspect for businesses. CRM has evolved gradually from Rolodexes of 1950s to Generative AI in 2020. What started as a record-keeping tool gradually evolved into digital documentation, sales automation, enterprise resource planning, and social marketing tools, to the present age hyper personalised automated communication form. The realm of CRM scope covers customer discovery, interactions, service, care, retention, and loyalty and is more often addressed as Digital CRM. In 2022, the worldwide size of CRM software stood at USD 96.3 billion. The Total Addressable Market is set to grow to USD 290 billion. Salesforce Inc, an early mover and a global market leader grew 10x in revenue in a decade. In 2013, its revenue stood at USD 3.1 billion which stands at USD 34 billion in FY 2022. CRM, which started as a simple Rolodex, has evolved into a complex system laced with artificial intelligence that helps organisations manage customer data and engage them with it in a self-assisted automated format, bringing huge implications for cost, efficiency, and the experience of consumer communication. Managing customer interactions with Gen AI and CRM Gen AI has the potential to enable a better connection between brands and customers. This however requires creative ability to engage customers and ability to execute to deliver better performance results and employee experiences. A combination of Gen AI and CRM can impact functional domains of marketing, sales, commerce, service, and customer success. Marketing Gen AI capabilities are ideally suited for the marketing function which requires content creation and creative generation. It will enable marketers increase their output, efficiency, and creativity. It provides a cost and time effective option for producing text, images, creative briefs, multiple versions of ad campaigns with variations. Most crucially, it will help marketers create personalised and engaging experience for customers at scale. Additionally, it will enhance idea creation, productivity and data driven planning and execution for marketing teams. Content development and personalisation of creatives will come at a reduced turn around time and cost. Conventional content creation methods which are time consuming, lack hyper personalisation at scale across multiple content formats with data driven insights on consumer behaviour. Brands are thus able to communicate through the most relevant content and most effective media at speed. Gen AI can create content across diverse platforms from blogs to social media posts to email campaigns, with a nuanced data backed understanding of the target audience and at the same time ensuring that the designed format, tone, and campaign outcomes are in sync. These elements are the most crucial for scale. Moreover, the ability to create versions of campaigns and content, marketers can execute A/B testing at speed and refine execution for optimal conversion. Ensuring standardisation of brand voice and tone with a synchronisation of specific target audience requirements with greater accuracy and speed, give Gen AI an edge over the conventional human creative teams. These are critical for brands with presence in multiple locations across different cultures and regional preferences. Real time sentiment analysis, that not only establishes positive , negative or neutral sentiment across key words and topics associated with the brand, but also analysis activation across broad competitive set to inform competitive benchmarking and rating. These insights make marketing teams better equipped to execute data insight driven campaigns. Tools for gen AI production are largely simplified and don’t require complex integrations into existing workflows. This, however, will require data management, tech stacks, governance, and operational capabilities for organisations to fully scale AI in marketing. Sales Product sales has evolved into providing tailored sales content across the customer’s early journey. Chatbots, real time Q&As, self-service portals, customised proposals and other features unlocked by Gen AI are not only reducing operational inefficiencies and administrative burdens but also enhancing the experience of purchasing products. Amongst key benefits of Gen -AI are : • Automation of administrative and lower value tasks like data entry, meeting notes, proposals, sales script etc. • Implementation and management of streamlined sales processes at scale across products and locations delivering features sales service value at a lower cost. • Training, onboarding and management of sales teams and resources can be done at speed and efficiency with increased standardisation in the sales pitches. • Channel partner and distribution networks managed across multiple territories and products. Channel networks can get personalised content, lead management support, incentive plans, and gamified leaderboards. Across the sale value chain Gen AI increases seller speed and productivity and also reduces the experience friction. Seller productivity gets efficiency by autoupdation of CRM using AI and machine leading to ensure that the sales pipeline data hygiene is maintained with a lesser administrative effort of data entries. It ensures, that there are smart prompts that aid pre-sales and sales team to enable them take brand specific , user insight driven and sales goal oriented actions. With Gen-Ais capabilities one case accurately gauge user interaction basis of past data and generate content tailored for the specific needs of the customers product or service requirements. Sales enablement Ensuring sales teams are equipped with the right set of product, service and consumer information with the right training content curated specifically to the sales member’s background. This is handy for large sales teams operating across multiple locations. With voice to text features, automated note taking, calendar and meeting management, sellers’ capacity is offloaded of administrative and low value work thus maximising capacity utilisation. Self-assisted customisation and configuration of products and services with real-time quotes and tailored pricing and offers ensure customer centricity in sales processes. The engagement becomes personalised, optimised and dynamic to the users requirements ensuring better experience of sale and probability of closure. Buyer profiling, with preferences and pattern analysis help sellers understand their needs and provide a tailored outreach. Bais of customers sentiment analysis from its communication forms of call transcripts and emails a probability of conversion and lead prioritisation helps sales teams prioritise their sales pipelines. Automated chatbots ensure human-like QnA experience with tailored yet standardised responses for customers ensuring they are kept engaged real-time and recommended products and services suited to their needs. Sales copilots also are an effective feature that help sales resources create specific communication to customer personas based on the stage of transaction. Commerce / transaction Every consumer engages digitally to consider or make a transaction. Gen AI features sets are reducing cart abandonment by delivering a hyper personalised buying experience with intuitive prompts by tailoring user journeys and promoting conversions. These tools ensure continuous engagement with the consumer for product information, comparison, pricing and delivery. Tools that help customers across intuitive search, personalised recommendations, enhanced feedback loop and streamlined shopping experience. Data driven personalises searches, recommendation and natural language bases search and recommendation options ensure quick transaction turnarounds. Product cataloguing and information listing becomes automated. Customers can also look at the products in 3 dimensions thus ensuring better visualisation and evaluation. With bespoke purchase plans, customer satisfaction and retention increase thus positively impacting sales numbers, experiences and band loyalty. Customer service and customer success Post transaction service experience becomes most critical for customers and brands alike considering the level of customised and tailored experiences that is brought on in the discovery and transaction phases of the user journeys. This is what leads to brand loyalty, repeatability of transactions and increased lifetime value of customers once onboarded on the brand or product portfolio. Prompt, real time and accurate self-service capabilities ensure faster customer grievance management and resolution. Virtual and human agents engaged in customer service are laced with fit-for purpose scripts, prompts, information, and training with automated tasks like follow up emails, and calls. This brings a multi fold increase to agent productivity. Gen AI and LLMs can analyse a customer’s profile and with automated workflows cater to their potential issues. With product catalogue assists there is an increase in cross sell and recommendations for customers increasing their wallet share efficiently. Agents are assisted with next best actions to ensure recommendations on additional products and features. The true potential of Gen AI can be unlocked best when used in combination with predictive AI, voice to text, experience management and workflow optimisation. In the customer success segment of the value chain, a faster time to value with efficient onboarding workflows ensure an improved customer experience and reduced customer churn. Training co-pilots, automated self assists bots and knowledge content driven prompts and actions ensure faster time to value realisation for customers. Given the depth and breadth of AI capabilities that can impact customers across the user journeys from marketing, sales, transactions, service and customer success, organisations and teams need to ensure that they are upskilled with tech , workflows and capabilities to deliver an enhanced customer experience. This can be ensured by doing 4 critical things. 1. What are the customer services opportunities one can identify, prioritise and phase for execution. 2. On identifying the use cases which are most critical for business objectives, the next important thing is to choose the platform or solution to deliver Gen-A features to for the specific use cases. Are these solutions meeting user needs? Does the organisation have the ability to deliver these? and do these solutions generate business goals an revenues. 3. On onboarding the solution or platform, one needs to ensure capability building to adopt, use and monitor the feature set. The resources, organisational structure and operating model required to deliver the solution. 4. Fourth, most crucial aspect is idenfitying risks of adoption and implementation and impact on customer from a compliance and governance stand point. Organisations that are constantly looking to improve customer interactions, create hyper personalised and differential experiences for their customers, and improve their operational efficiency will be the fastest to catch on to the Gen-AI driven revolution in customer relationship management space. Customers are ready , can organisations upskill, upgrade and uplift their game ?
PropTech Pulse Editorial
25th April 2024
Market Trends
Proptech Market Growth, Trends & Forecast Analysis
Key Insights into the PropTech Market Let’s dig into the core factors driving this digital revolution. These insights will help you keep up with market changes and take advantage of growth opportunities. Market Overview and Growth Outlook As the real estate market evolves, the demand for tech-driven solutions has reached an all-time high. This shift isn't just a passing trend. Rather, it's a response to the realities of a fast-paced industry. With an impressive 16% compound annual growth rate (CAGR), the appetite for real-time data, operational efficiency, and enhanced customer experiences is propelling property managers, agents, and investors to adopt innovative technology. So, what are they really after? It’s simple → streamlined operations, reduced costs, and a user experience that keeps clients coming back for more. PropTech Market Growth - Factors and Challenges To understand this growth story, we need to look at two pivotal elements driving this expansion. AI and Machine Learning Adoption The adoption facilitates predictive analytics and personalized property recommendations, significantly impacting decision-making processes. A recent McKinsey report highlights that real estate companies leveraging AI have boosted their net operating income by over 10%. This improvement stems from enhanced operational efficiencies, allowing firms to make smarter investment decisions and better allocate resources. Cloud-Based Solutions Demand Next, the demand for cloud-based property management systems is growing, offering flexibility and scalability that traditional on-premise solutions struggle to match. This shift is evidenced by industry leaders who prioritize innovation and customer-centric strategies. Reflecting this shift, AppFolio closed Q4 2022 with a 30% revenue increase, reaching $124.1 million — a clear indicator of how cloud solutions are shaping the future. However, this overall PropTech market growth is not without its challenges. 78% of real estate professionals are concerned about cyber attacks. Issues such as cybersecurity threats, data privacy concerns, and a lack of regulatory framework for AI applications necessitate a vigilant approach to risk management. Balancing innovation with security will be key to leveraging the full potential of PropTech, ensuring that as we move forward, we do so with confidence. Impact of Digital Transformation on Real Estate Exploring properties from your couch or submitting an offer on a home while sipping coffee is now part of everyday life in real estate. This shift in consumer behavior compels real estate professionals to rethink their strategies and embrace new digital-first methods. Blockchain technology is one such advancement that stands out as a key player in enhancing transaction transparency. Platforms such as Propy are pioneering cross-border real estate transactions, streamlining the buying process and building trust among buyers and sellers. These advancements simplify what once were complex processes, making real estate more accessible than ever. Market Segmentation and Analysis Exploring PropTech market segments isn’t just for industry insiders. Therefore let’s look at the major segments shaping PropTech today, seeing who’s using what, the impact, and why it matters. Integrated Platforms vs. Standalone Software In the PropTech market, two solutions lead the way: More and more professionals in the industry are opting for integrated systems. Why? Because they help eliminate data silos and simplify cross-department communication. Real estate players recognize that integrated platforms allow for real-time oversight, helping them to scale operations without juggling multiple tools. All of which a standalone software cannot provide. Now, the issue in question is whether to choose a cloud-based or on-premise PropTech solution! Cloud-Based vs. On-Premise Solutions Cloud-based PropTech software solutions have become the preferred choice, making up 69% of real estate software deployments in 2023. The preference shift is largely due to the cloud’s scalability, lower upfront costs, and flexible access points. Sure, on-premise solutions still have their place in highly regulated markets, but even those are slowly giving way to the convenience of the cloud. Residential, Commercial, and Industrial Markets Building on these trends, each real estate market — residential, commercial, and industrial — has a unique PropTech adoption curve. Here’s how they differ: Residential Market: By 2022, residential PropTech had a substantial 58% market share, with platforms streamlining property listings, virtual tours, and tenant management. Zillow and Redfin continue to innovate, integrating AI-based virtual staging and 3D walkthroughs, attracting tech-savvy homebuyers. Commercial Market: Smart building solutions are on the rise, particularly in offices. Incorporating IoT to monitor energy use and enhance tenant engagement. Industrial Market: Logistics and warehouse management are increasingly adopting PropTech, though growth is still catching up to residential and commercial sectors. The focus is on enhancing inventory tracking, security, and operational efficiency. Real Estate Agents, Property Investors, and More In the past few years, PropTech solutions have reshaped the role of real estate agents and property investors: Real Estate Agents: Tools like Matterport for 3D virtual tours and automated valuation models (AVMs) for faster price analysis are empowering agents to enrich the client experience. In a recent survey, real estate agents reported 40% improved lead conversion rates after integrating virtual tours. Property Investors: With access to predictive analytics, investors are making data-backed decisions like never before. Platforms such as CompStak provide insights into leasing comps and market trends, helping investors reduce risks and maximize returns. Regional Insights: PropTech Growth Across the Globe PropTech is booming worldwide, but its growth trajectory looks different depending on where you are. North America: Key Market Drivers and Trends The USA is home to several leading PropTech firms. However, North America, in particular, is the leading hub for PropTech innovation, accounting for over 55% of global market share. Smart building technology Blockchain-based transactions These trends are particularly visible in tech-driven cities like San Francisco and New York due to their sustainable features. PropTech Growth in Europe: Challenges and Opportunities Europe’s PropTech market is expected to grow significantly, focusing on: Sustainable building solutions Green technology integration Countries like the UK and Germany are leading the charge, though regulatory hurdles and varying property laws across nations pose challenges for market expansion. The Fast-Paced Expansion in Asia-Pacific Markets With a 17% projected CAGR through 2030, Asia-Pacific is the fastest-growing PropTech region. Urbanization, rising incomes, and government-backed digital infrastructure in countries like China, Japan, and India fuel this surge. Emerging PropTech Markets in Latin America and Africa PropTech in Latin America and Africa is still in its early stages but shows potential. Mobile-first solutions for underserved markets are accelerating digital transformation in residential housing. PropTech Market Forecast: Trends to Watch Through 2034 After observing the trends, it's clear that the future of the PropTech market is evolving. Let’s take a closer look at the trends that are set to shape the industry over the next decade. Residential Property Market Outlook and Key Trends Imagine walking into a home where everything is automated, from lighting to temperature control. Key trends include: Home automation AI-based property recommendations Seamless remote management By 2030, virtual reality (VR) tours are expected to become a standard part of the buying process, making home shopping feel like a game rather than a chore. The Rise of Smart Building and IoT-Enabled Solutions The global demand for Internet of Things (IoT)-enabled smart buildings is expected to grow, with an increasing focus on: Energy management Tenant experience Predictive maintenance In 2022, about 307.8 million users engaged with IoT in smart homes — an impressive 88% jump since 2018. Competitive Landscape in the PropTech Industry Competition in PropTech is heating up, with both startups and established companies battling it out for market share. The real differentiator? Innovation. Companies that use: Data analytics AI Automation are enhancing the customer experience and coming out on top. Key Players in the PropTech Market Leading players in the PropTech market include: Opendoor Aurum PropTech These companies drive innovation with AI-based valuation models and blockchain transaction systems. Strategic Partnerships and Mergers in the PropTech Sector One trend to keep an eye on is strategic partnerships. For example: Opendoor and Redfin: Combining buying platforms with brokerage services to streamline real estate processes. JLL Technologies' acquisition of Building Engines: Strengthening capabilities in property management. Such collaborations reflect broader strategies to consolidate resources and enhance operational efficiency and customer experience. Similarly, JLL Technologies' acquisition of Building Engines underscores how companies are leveraging mergers to strengthen their capabilities in property management, highlighting the industry’s move toward more comprehensive, end-to-end tech solutions. New Entrants and Innovation in PropTech Solutions Startups focused on sustainable PropTech and decentralized real estate platforms are particularly notable. While established companies still dominate, these new entrants are offering fresh, innovative ways to buy, sell, and manage properties. With these partnerships and new entrants, it’s crucial to look ahead at the trends influencing the PropTech market in 2024. PropTech Market Trends in 2024 & What’s Next So, where is the PropTech market headed? Changing consumer expectations and technological advancements will continue to push the industry forward. Here are a few key trends to watch. Trend 1: The Impact of AI and Machine Learning in PropTech Enhanced Accuracy: AI improves tenant screening and property valuations. Predictive Insights: Machine learning analyzes trends, reducing risks. Focus on Strategy: Automating routine tasks allows professionals to strategize. Cost Efficiency: Lower operational costs through automation. Increased ROI: Better data leads to informed investment decisions. Trend 2: Blockchain and Real Estate: Revolutionizing Transactions Improved Transparency: A decentralized ledger enhances trust in transactions. Smart Contracts: Automates title management and escrow processes. Reduced Costs: Eliminates intermediaries, lowering transaction fees. Faster Closures: Speeds up the buying and selling process. Future Standardization: By the 2030s, blockchain will dominate real estate contracts. Trend 3: PropTech Adoption in Property Management and Investment Meeting Expectations: PropTech caters to the digital-native tenant demographic. Real-Time Data: IoT sensors help managers address issues proactively. AI-Driven Insights: Platforms provide market insights for investors. Optimized Returns: Streamlined processes enhance investment profitability. Tenant Satisfaction: Improved management leads to higher tenant retention. Trend 4: PropTech’s Role in the Post-Pandemic Real Estate Market Lasting Changes: Remote management and virtual tours become standard. Increased Demand: Consumers expect more convenience and efficiency. Long-Term Growth: The sector continues to expand due to changing needs. Innovative Solutions: New technologies emerge to address evolving challenges. Cultural Shift: A new norm is established in property interactions. Trend 5: The Future of Smart Cities and PropTech Solutions Urban Optimization: IoT helps manage traffic and energy usage. Sustainability Goals: PropTech contributes to eco-friendly city planning. Enhanced Quality of Life: Improved services and infrastructure for residents. Data-Driven Planning: City planners leverage real-time data for decisions. Collaborative Growth: Partnerships between PropTech and city planners increase. Trend 6: Sustainability and Green Tech in the PropTech Market Energy Efficiency: Focus on retrofitting buildings to reduce consumption like Sustainability Partners. Consumer Preference: Growing demand for eco-friendly solutions. Market Influence: Companies aligning with sustainability gain market traction. Carbon Footprint Reduction: Green tech initiatives lower environmental impact. Regulatory Support: Increasing regulations favor sustainable practices in real estate. In a nutshell The PropTech market is set for significant growth and change. As consumer expectations shift and technology advances, stakeholders need to stay flexible and creative to succeed. Looking ahead, the emphasis will be on sustainability, automation, and incorporating new technologies. As a leader in digital transformation, Aurum PropTech is revolutionizing the real estate landscape with innovative solutions. With over 14 cutting-edge products, like Aurum PropTech Pulse, and an impressive 75% share of India's PropTech market potential, Aurum is on the road to redefining the future of real estate.
PropTech Pulse Editorial
1st January 2025
Technology and Innovation
Evolution of Customer Relationship Management tools
‘‘The purpose of a business is to create and keep a customer’’, Peter Drucker, a famous writer, and management consultant said prolifically. The realm of CRM scope covers customer discovery, interactions, service, care, retention, and loyalty. The term Customer Relationship Management (CRM) was coined in the early 1970s when management at business units realized it would be better to be customer emphatic rather than product emphatic. Customer relationship management tools has evolved gradually from Rolodex’s of 1950s to Generative AI in 2020. What started as a record-keeping tool gradually evolved into digital documentation, sales automation, enterprise resource planning, social marketing, to the present age hyper personalised automated communication form. 1956 - First CRM Gadget - Rolodex In 1956s, Danish engineer Hildaur Neilsen, chief engineer of Zephyr American invented Rolodex, a card index system used to store customer contact information. It was a desk gadget that stacked and stored business cards and index cards that people could spin and flip through. Digital Rolodex, Tele sales and advent of computers The 1980s saw an evolution in sales, marketing and customer retention tactics with the advent of digitisation. Tools such as direct mail, brochures, and product catalogues being sent to a database of customers to get them to buy something were prevalently used in the 1980s. Database marketing and digital Rolodex came to the fore. The late 1980s saw the advent of telesales for customer communication. Computers were also accessible for enterprises and became a means of storing information about customers. In 1987, the software programme ACT (Activity Control Technology) was created by Mike Sullivan and Mitch Muhney, officially known as the first CRM software. This was essentially a digital Rolodex that allowed storage and management of the entire customer lifecycle information on the software. With its usage of Customer Relationship Management software, Act! demonstrated the advantages of scalable software that utilized consumer information to help a firm better manage its connections. 1990 - Sales Automation and progression into CRM systems By 1990s, one saw a progression of database management into customer lifecycle management and sales force workflow automation. Tools like enterprise resource planning, and marketing were added to the software’s contact management functions. This was the emergence first CRM systems. Tom Siebel, founder of Sieble Systems, coined the term CRM (Customer Relationship Software) for the first time. The post-introduction of the same CRM took off exponentially, with other companies also providing CRM solutions. Siebel Systems was later acquired by Oracle for over USD 5 billion in 2005. Late 1900s - First Mobile CRM, SaaS business model and Salesforce Inc. Post invention of PDA (Personal Digital Assistant) devices, tasks, emails, and calendar management became mobile. It allowed sales individuals to access customer data from central databases on the go, which proved to be a game changer as one didn’t have to be on the desk to work out these tasks. Salesforce.com was launched in 1999 and offered a new business model, offering software services as subscriptions (SaaS), wherein the upfront implementation cost, effort, and maintenance would be taken care of by Salesforce. 2000 - Cloud based CRM, Open-Source CRM and Social CRM In 2007, internet boom and cloud storage led to the advent and proliferation of Cloud-based CRM. With the increased internet adoption, Salesforce’s subscription model became popular as it could be scaled up very quickly. Open-source software also came to the fore, with the most prominent one being Sugar CRM, invented by computer scientists and ex-IBM and Hewlett-Packard employees Clint Oram, John Roberts, and Jacob Taylor. With the increased proliferation, and exponential growth of social media platforms, CRMs were combined with social media tools to offer SCRM. 2010 - Artificial Intelligence and CRM Artificial intelligence (AI) has changed the CRM space substantially with automation and intelligence. AI can be used for lead scoring, identifying customer needs, and providing recommendations. With enormous data being generated across every consumer by way of their digital footprint, CRM with AI and data analytics makes it simple to extrapolate consumer behaviour and requirements in real-time. 2020 and Now - Generative AI Generative AI is a subset of AI but unique in its ability to learn from underlying patterns to create new data that mirrors the training data set. The power of creation has a multifold impact across industries, and consumer communication is only to benefit from this capability. Managing customer interactions with Gen AI has the potential to enable a better connection between brands and customers. This however requires creative ability to engage customers and ability to execute to deliver better performance results and employee experiences. A combination of Gen AI and CRM can impact functional domains of marketing, sales, commerce, service and customer success. The true potential of Gen AI can be unlocked best when used in combination with predictive AI, voice to text, experience management and workflow optimisation. The CRM journey has reached an interesting point with AI, and the future looks promising for this space. The Total Addressable Market is set to grow to USD 290 billion by 2026. Salesforce Inc, an early mover, and a global market leader grew 10x in revenue in a decade. In 2013, its revenue stood at USD 3.1 billion which stands at USD 34 billion in FY 2022. CRM, which started as a simple Rolodex, has evolved into a complex system laced with artificial intelligence that helps organisations manage customer data and engage them with it in a self-assisted automated format, bringing huge implications for cost, efficiency, and the experience of consumer communication. As we advance further into the coming decades, CRM software systems will become more intelligent, integrated and intuitive with powerful AI capabilities, greater emphasis on self-service, enhanced experience for customers, hyper-personalisation, integrated API networks and ecosystems, and a single source of truth for businesses. Peter Drucker will be smiling in his grave looking at the advancement in this space.
PropTech Pulse Editorial
12th April 2024
Technology and Innovation
Gen AI and the Changing Landscape of CRM
‘‘The purpose of a business is to create and keep a customer’’, Peter Drucker, a famous writer, and management consultant. Every business, lives, profits and grows with this mantra. Business that succeeded across all the previous industrial revolutions including mechanisation, electrification, automated production, and computation have one common trait. Each of this business not only changed consumer lives but also the experience of interaction with the business and utilisation of its product or service. So, what changes today, in the 4th industrial revolution that was set off by the advances in computing and information and communication technology and is built on 4IRs. Firstly, connectivity, data and computational power, second - analytics and intelligence, third human–machine interaction and fourth - advanced engineering. These form the 4 pillars of Industry 4.0. Technology, is only half of what businesses have to adopt and change. Two additional major factors that change the business environment are, customer demographics and behaviours and introduction of new business models. Marketing and sales strategies have fundamentally aligned on to the consumer behaviour of wanting goods and services on demand and scarcity of time and attention span. Information and content is delivered and consumed on mobile phones, with GenZ and Millennial tech savvy consumers attending only to content that they find targeted, relevant and authentic. Customers of today, in addition to goods and service also want convenience, self-service and personalisation. Some common traits of the contemporary customer are, that they are well informed and self-educated, self-directed, fast paced, picky, contradictory, always connected, volatile and tech innate. Beyond product and service innovation, new business models like freemium, pay-per-use, low monthly subscriptions are engaging consumers continuously to ensure sustainable revenue streams, reaching profitability and turning recent adopters into loyal customers. Thus, ensuring long lasting relationships with customers have become a key aspect for businesses. CRM has evolved gradually from Rolodexes of 1950s to Generative AI in 2020. What started as a record-keeping tool gradually evolved into digital documentation, sales automation, enterprise resource planning, and social marketing tools, to the present age hyper personalised automated communication form. The realm of CRM scope covers customer discovery, interactions, service, care, retention, and loyalty and is more often addressed as Digital CRM. In 2022, the worldwide size of CRM software stood at USD 96.3 billion. The Total Addressable Market is set to grow to USD 290 billion. Salesforce Inc, an early mover and a global market leader grew 10x in revenue in a decade. In 2013, its revenue stood at USD 3.1 billion which stands at USD 34 billion in FY 2022. CRM, which started as a simple Rolodex, has evolved into a complex system laced with artificial intelligence that helps organisations manage customer data and engage them with it in a self-assisted automated format, bringing huge implications for cost, efficiency, and the experience of consumer communication. Managing customer interactions with Gen AI and CRM Gen AI has the potential to enable a better connection between brands and customers. This however requires creative ability to engage customers and ability to execute to deliver better performance results and employee experiences. A combination of Gen AI and CRM can impact functional domains of marketing, sales, commerce, service, and customer success. Marketing Gen AI capabilities are ideally suited for the marketing function which requires content creation and creative generation. It will enable marketers increase their output, efficiency, and creativity. It provides a cost and time effective option for producing text, images, creative briefs, multiple versions of ad campaigns with variations. Most crucially, it will help marketers create personalised and engaging experience for customers at scale. Additionally, it will enhance idea creation, productivity and data driven planning and execution for marketing teams. Content development and personalisation of creatives will come at a reduced turn around time and cost. Conventional content creation methods which are time consuming, lack hyper personalisation at scale across multiple content formats with data driven insights on consumer behaviour. Brands are thus able to communicate through the most relevant content and most effective media at speed. Gen AI can create content across diverse platforms from blogs to social media posts to email campaigns, with a nuanced data backed understanding of the target audience and at the same time ensuring that the designed format, tone, and campaign outcomes are in sync. These elements are the most crucial for scale. Moreover, the ability to create versions of campaigns and content, marketers can execute A/B testing at speed and refine execution for optimal conversion. Ensuring standardisation of brand voice and tone with a synchronisation of specific target audience requirements with greater accuracy and speed, give Gen AI an edge over the conventional human creative teams. These are critical for brands with presence in multiple locations across different cultures and regional preferences. Real time sentiment analysis, that not only establishes positive , negative or neutral sentiment across key words and topics associated with the brand, but also analysis activation across broad competitive set to inform competitive benchmarking and rating. These insights make marketing teams better equipped to execute data insight driven campaigns. Tools for gen AI production are largely simplified and don’t require complex integrations into existing workflows. This, however, will require data management, tech stacks, governance, and operational capabilities for organisations to fully scale AI in marketing. Sales Product sales has evolved into providing tailored sales content across the customer’s early journey. Chatbots, real time Q&As, self-service portals, customised proposals and other features unlocked by Gen AI are not only reducing operational inefficiencies and administrative burdens but also enhancing the experience of purchasing products. Amongst key benefits of Gen -AI are : • Automation of administrative and lower value tasks like data entry, meeting notes, proposals, sales script etc. • Implementation and management of streamlined sales processes at scale across products and locations delivering features sales service value at a lower cost. • Training, onboarding and management of sales teams and resources can be done at speed and efficiency with increased standardisation in the sales pitches. • Channel partner and distribution networks managed across multiple territories and products. Channel networks can get personalised content, lead management support, incentive plans, and gamified leaderboards. Across the sale value chain Gen AI increases seller speed and productivity and also reduces the experience friction. Seller productivity gets efficiency by autoupdation of CRM using AI and machine leading to ensure that the sales pipeline data hygiene is maintained with a lesser administrative effort of data entries. It ensures, that there are smart prompts that aid pre-sales and sales team to enable them take brand specific , user insight driven and sales goal oriented actions. With Gen-Ais capabilities one case accurately gauge user interaction basis of past data and generate content tailored for the specific needs of the customers product or service requirements. Sales enablement Ensuring sales teams are equipped with the right set of product, service and consumer information with the right training content curated specifically to the sales member’s background. This is handy for large sales teams operating across multiple locations. With voice to text features, automated note taking, calendar and meeting management, sellers’ capacity is offloaded of administrative and low value work thus maximising capacity utilisation. Self-assisted customisation and configuration of products and services with real-time quotes and tailored pricing and offers ensure customer centricity in sales processes. The engagement becomes personalised, optimised and dynamic to the users requirements ensuring better experience of sale and probability of closure. Buyer profiling, with preferences and pattern analysis help sellers understand their needs and provide a tailored outreach. Bais of customers sentiment analysis from its communication forms of call transcripts and emails a probability of conversion and lead prioritisation helps sales teams prioritise their sales pipelines. Automated chatbots ensure human-like QnA experience with tailored yet standardised responses for customers ensuring they are kept engaged real-time and recommended products and services suited to their needs. Sales copilots also are an effective feature that help sales resources create specific communication to customer personas based on the stage of transaction. Commerce / transaction Every consumer engages digitally to consider or make a transaction. Gen AI features sets are reducing cart abandonment by delivering a hyper personalised buying experience with intuitive prompts by tailoring user journeys and promoting conversions. These tools ensure continuous engagement with the consumer for product information, comparison, pricing and delivery. Tools that help customers across intuitive search, personalised recommendations, enhanced feedback loop and streamlined shopping experience. Data driven personalises searches, recommendation and natural language bases search and recommendation options ensure quick transaction turnarounds. Product cataloguing and information listing becomes automated. Customers can also look at the products in 3 dimensions thus ensuring better visualisation and evaluation. With bespoke purchase plans, customer satisfaction and retention increase thus positively impacting sales numbers, experiences and band loyalty. Customer service and customer success Post transaction service experience becomes most critical for customers and brands alike considering the level of customised and tailored experiences that is brought on in the discovery and transaction phases of the user journeys. This is what leads to brand loyalty, repeatability of transactions and increased lifetime value of customers once onboarded on the brand or product portfolio. Prompt, real time and accurate self-service capabilities ensure faster customer grievance management and resolution. Virtual and human agents engaged in customer service are laced with fit-for purpose scripts, prompts, information, and training with automated tasks like follow up emails, and calls. This brings a multi fold increase to agent productivity. Gen AI and LLMs can analyse a customer’s profile and with automated workflows cater to their potential issues. With product catalogue assists there is an increase in cross sell and recommendations for customers increasing their wallet share efficiently. Agents are assisted with next best actions to ensure recommendations on additional products and features. The true potential of Gen AI can be unlocked best when used in combination with predictive AI, voice to text, experience management and workflow optimisation. In the customer success segment of the value chain, a faster time to value with efficient onboarding workflows ensure an improved customer experience and reduced customer churn. Training co-pilots, automated self assists bots and knowledge content driven prompts and actions ensure faster time to value realisation for customers. Given the depth and breadth of AI capabilities that can impact customers across the user journeys from marketing, sales, transactions, service and customer success, organisations and teams need to ensure that they are upskilled with tech , workflows and capabilities to deliver an enhanced customer experience. This can be ensured by doing 4 critical things. 1. What are the customer services opportunities one can identify, prioritise and phase for execution. 2. On identifying the use cases which are most critical for business objectives, the next important thing is to choose the platform or solution to deliver Gen-A features to for the specific use cases. Are these solutions meeting user needs? Does the organisation have the ability to deliver these? and do these solutions generate business goals an revenues. 3. On onboarding the solution or platform, one needs to ensure capability building to adopt, use and monitor the feature set. The resources, organisational structure and operating model required to deliver the solution. 4. Fourth, most crucial aspect is idenfitying risks of adoption and implementation and impact on customer from a compliance and governance stand point. Organisations that are constantly looking to improve customer interactions, create hyper personalised and differential experiences for their customers, and improve their operational efficiency will be the fastest to catch on to the Gen-AI driven revolution in customer relationship management space. Customers are ready , can organisations upskill, upgrade and uplift their game ?
PropTech Pulse Editorial
25th April 2024
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