Aliseda: Optimising commercial management thanks to technology

Projects

Aliseda

Starting point

A need for greater knowledge of leads and their commercial flow, increasing conversion and campaign effectiveness.

Solution

Building a data lake with diverse data sources that helped to better identify opportunities, increase efficiency and improve the ROI of the campaigns.

What we did

Strategy
Design
User Experience
Analytics

Selling more and better: that sums up the challenge that Aliseda Real Estate presented to us. That goal, far easier said than done, would be fulfilled by designing and implementing a new operational model for the marketing and sale of real estate. This model would drive growth in sales, improve quality of service and customer experience, and increase control over operations.

Our solution had a seemingly simple front, created to provide Aliseda’s workers with tools to improve the management of the relationship with the client at any point in the customer journey. However, this is only the most visible part of extensive work in the back, which consisted of redesigning and optimising the entire technological ecosystem on which this client knowledge is based.

An ambitious and complex technological project which, based on the consumption of real-time data, served to deepen the knowledge of leads and customers, identify the best opportunities in the commercial flow, increase the efficiency and agility of the campaigns and, ultimately, improve business intelligence.

A radical improvement in customer knowledge and contact points allowed us to increase conversions.

How do we improve knowledge of the client?

The development of an all-channel platform on which to display a complete knowledge of the client was the cornerstone of the renewal of the digital strategy. To build it, we conducted an in-depth analysis of Aliseda’s customer journey, identifying all of the points of contact and the channels of interaction for each of them. We then defined a strategy aimed at collecting information from each of these points of contact. We created a monitoring process of each property in which the user showed interest, with its own workflow within the life cycle, recorded in the history of interaction with the customer.

For accesses through the portal, we designed a digital fingerprint tracking system that registered the interactions of each user, which allowed us to have the history of each one of them (visits to the web, characteristics of the searched properties, campaigns with which they had been impacted, etc.). This allowed us to personalise the commercial information provided to each user.

The call centre was another important point of contact. We developed an interface aimed exclusively at call centre employees, so that the operator could see the user’s customer file when talking to them. All the user’s interactions were recorded on the file, as well as the scoring assigned to each lead at the time of authentication. During the conversation, the customer service operators detailed the information gathered about each customer, and could qualify or modify attributes on their file.

Let’s not forget another moment of vital importance when it comes to refining the knowledge of the client: the visit to the property. In order to define the parameters of a physical event like that, we developed an application aimed at Aliseda’s representatives, so that they had access from their mobile devices to all the information about each client. At the end of the visit, they filled out a questionnaire with precise data about the lead (Do you have children? Will you take out a mortgage? Are you buying to live or to invest?), refining their profile even more.

What did we do with all this data?

All the information compiled in the previous processes (web traffic, call centre, commercial network) was dumped into a data lake, a unique repository for real-time storing and grouping of all the data and interactions obtained along the customer journey, which we built using Cassandra (database management) and Storm (data flow process) technology.

Additionally, as a complement to the data lake, we developed a Business Intelligence (BI) model that included analytical and predictive tools for the exploitation of information (Pentaho). This was used to develop a complete business scorecard, automated and in real-time. The tool defined rules of interaction based on the position of each lead in the journey map (recruitment / conversion / investment) and the ROI of each digital channel.

In turn, we designed the marketing automation strategy. We integrated the information contained in the data lake and the interaction rules defined by the BI module, using IBM Watson Campaign to automate the marketing campaigns and impact each lead with the optimal content and actions according to its position in the conversion funnel. Interactions with commercial communications were also integrated into the data lake, in order to enrich the customer file and assign impact tracking in an attribution model.

“Interactions with commercial communications were also integrated into the data lake, in order to enrich the customer file”.

The final result: lead optimisation

The centralisation and processing of data made it possible to develop all-channel (call centre, marketing, sales network) recommendation systems. These provided commercial support and carried out communication actions aimed at the needs of each client in real-time, improving the user experience at all times.

On the other hand, the analysis of the conversion funnel made it possible to measure the profitability of the shares in an agile way, increasing the conversion ratio thanks to the personalised follow-up of each client and the consequent improvement of the experience.

In short, we built a new technological environment based on the development and evolution of innovative and efficient tools, helping to generate a real impact on the business of Aliseda.

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