Customer data re-activated: sales and marketing stack for hypergrowth

In 2019, Bo LKV Group started researching how to better support their marketing, sales and customer service processes by utilising customer data effectively. Customer data was scattered across different systems and lacked real-time integrations and, most of all, modern tools to utilise the data.

Columbia Road and Bo LKV partnered first to find out what concrete use cases would provide customers and real estate agents more value in lead generation, lead nurturing and high-quality customer interactions over the whole lifecycle of real estate sellers and buyers. Secondarily, our objective was to activate the existing data about customers and their transaction data and combine that with data from digital and offline engagements to fuel new use cases.

Concrete targets for our collaboration

• Automate high-value customer-facing processes around real estate
• Make sales processes more efficient to support realtors in their work
• Gather key customer data into a platform where it can be utilised for marketing and sales
• Support lead generation and marketing across the whole customer journey
• Capabilities to utilise customer and associated sales data

Our approach

Finding high-value use cases

Right from the start, we found out that Bo LKV had a substantial amount of data that was not actively utilised. Out of the data, it was important to recognise key elements and attributes that should be extracted, transformed and loaded to a modern platform. Rather than taking a bottom-up approach, such as an extensive data mapping exercise, we started from a business perspective: recognising the most important use cases for personalisation and automation.

We recognised HubSpot as a challenger platform to utilise the data across Bo’s customer touchpoints and make the data accessible internally by various functions, along with the 200 realtors. Based on the concrete sales and marketing use cases, we elaborated on how data needs to be transformed to fit the APIs and data models provided by HubSpot.

Although the focus was on selecting vertical end-to-end use cases for data utilisation, we also started to plan a scalable model where key data could be utilised for future needs to optimise and automate marketing and sales activities.

Getting deep with customer data

To make the integrations work in real-time, we decided to build a custom integration layer, a middleware, that gathers data from various back-end and 3rd party systems. On top of integrations, the middleware transforms the customer data into a usable format for Bo’s HubSpot. The solution consolidates duplicated customer data, marketing permissions and related transaction data into a single customer view that can be trusted when utilising the automation capabilities of HubSpot.

An integration layer was needed to process the data for real-time needs due to interface and query limitations of existing legacy back-end systems. To build high-performance middleware, the tech stack chosen for this purpose was Node.js, Heroku and MongoDB. Middleware was complemented with 3rd party integrations to enrich transaction data with 3rd party customer engagement metrics - enabling the utilisation of 3rd party data about apartment interest.

While building the backend integration layer, we did not hesitate to use HubSpot features for other concrete sales and marketing experiments. We incrementally started to onboard agents to various features, for example, by digitalising traditional offline lead processes, where leads are gathered from apartment showings. This allowed us to prove the versatility of HubSpot for various use cases and shorten the time to value.

Further development

Columbia Road and Bo LKV have continued the partnership by utilising further HubSpot capabilities. From the get-go, one of the recognised key challenges of Bo LKV’s efficient utilisation of HubSpot was the lack of standard functionality in the platform to support a “two-sided” business model. In real estate, deals, meaning apartment transactions, have both a seller and a buyer. Both are important segments to serve when growing the business as, more often than not, customers cross over from sellers to buyers and vice versa in the heated housing markets.

In late 2021 it was recognised that upcoming HubSpot features could enable more use cases: the possibility of using association labels between the objects. Together, we enrolled Bo LKV in a beta program and were quickly able to ramp up the feature. Knowing the legacy data we already had worked with, we had a clear idea of how to transform backend data and incorporate new endpoints into our integration layer so that the buyer and seller associations could be made with deals. This opened up a whole new set of use cases for marketers to create impactful customer experiences for both apartment sellers and buyers.

Technologies utilised in the project

• HubSpot CRM, Sales, Marketing and Service Hubs
• Heroku
• Node.js
• MongoDB
• Google Analytics Reporting API
• 3rd party REST APIs

Impact

The impact of modern sales and marketing capabilities, where the heavy lifting is done in the backend, is that marketing and sales can rely on the data in their daily operations. This ultimately creates value through automated and highly personalised engagements across the whole customer journey.

In our collaboration, we consciously avoided bubblegum solutions that would stretch the limits of HubSpot's standard data model. Instead, we aimed for the best-of-breed solution that provides value for the years to come. The robustness of the customer data setup brings new use case ideas to life faster. In combination with HubSpot’s great user experience, this makes the customer data come to life with concrete use cases where leads are nurtured, and customer value can be increased.

Highlights

• Holistic customer view for marketers and real estate agents, comprised of transactional data and engagement data
• Fully digitalised lead-gathering processes for 200+ real estate agents' personalised touchpoints for apartment showings
• Enabling and implementing various automation use cases and personalised digital nurturing models for different types of customers
• Customer consolidation, customer lifecycle management, marketing consent management