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Tenant satisfaction is one of the most important parts of being successful in the social housing industry, as it often leads to a higher CSAT (customer satisfaction score) which alone has numerous benefits outlined in some of our previous blogs. However, in order to ensure that your tenants are satisfied, active involvement from your organisation is necessary.
In the UK alone, the number of long-term vacant homes has risen by over 30,000 in the last 5 years. Although the worldwide pandemic has contributed to this statistic, it is continuing to grow at a staggering rate despite the recent slowdown in cases. While not apparent at first sight, the repercussions of this statistic are significant. From a societal standpoint, consequences range from an increased frequency in crime to decreased tax revenue and overall quality of public services.
In the realm of marketing, personalisation is key. By tailoring your company’s products and services to the unique needs of your customers, better content will be developed, customer experience will be enhanced, and revenue will significantly increase. In order to do this, marketers require one important tool: data. But with big data becoming more and more prevalent in today’s digital society, marketers need a way to effectively organise such data into a coherent and comprehensible manner.
Big data is immense, both in volume and complexity. As such, it can often be a difficult resource to store, manage, and utilise effectively. To address this obstacle, however, the practice of data integration has been developed, whose role is to prevent the mismanagement of big data by consolidating it. This blog will focus on the challenges of data integration, but before doing so, we will provide a basic outline and example of the data integration process.
Organisations that wish to remain competitive and relevant in the market are embracing big data. However, there is sometimes a disconnect between the management of data and the practical application of what that data can do for a company. It is the role of data integration to bridge that gap, permitting the data to be far more useful than it was previously.
