Real estate firm, Mizizi Africa Homes has announced plans of deploying big data to boost the efficiency of its operations and offer custom solutions to prospective homeowners.
The developer has today said it is seeking to understand existing and new clients better by analysing their dream home preferences, purchase history and financial status to help it make more intelligent recommendations on personalised products and pricing structure.
“Our plan is to ensure that we provide customers with the services they really need at affordable cost. We believe by analysing and processing information about homeowners we will be able to personalise our offerings,” said Mizizi Africa Finance and Operations Director, George Mburu.
The leading developer offering affordable off-plan homes has emerged the best in two national real estate awards in 2019 for transforming the way it engages and offer value to its clientele.
It was ranked as the most improved real estate developer in the use of digital solutions during the third digital tech excellence awards held on December 5, 2019 at the Intercontinental Hotel, Nairobi.
The awards, organized by Digital Events, recognizes SMEs and corporates making use of digital solutions to offer services in an efficient and convenient manner and to transform the lives of their clients.
Mizizi trounced competitors for maximising use of diverse digital platforms including Google, Facebook, Twitter, YouTube and leveraging on an interactive website that have facilitated instant responses to client queries, uploading new project updates and seamless engagement with customers.
In August, the company was voted the most promising housing developer in the country during the second annual Real Estate Excellence Awards 2019 held in Nairobi.
“We seek to foster and strengthen customer engagement, trust and loyalty in line with our commitment to involve prospective buyers in the entire construction process and offering competitive prices on properties,” said Mburu.
Under the new plan, Mizizi will monitor social networks using big data algorithms to complement traditional customer history in collecting more information to support predictive analytics that will guide the company in making better business decision.
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