According to McKinsey’s e-book “Big Data, Analytics, and the Future of Marketing & Sales”, $200bn of additional revenue is available to companies who put data at the centre of their marketing and sales decisions.
Leveraging big data and customer insights can be a game changer, to put these statistics in real-life business case studies that will resonate; the business social network LinkedIn uses the data from its hosted digital CVs and profiles, combined with job postings and recruiters to provide an all-round professional service to customers unavailable anywhere else. 25% of Hilton’s most loyal hotel guests regularly use its Hilton HHonors app to open doors, select rooms, check-in, and order services using their smart phones for a tailored experience.
But where to start with these so-called actionable insights from data?
Consumers today are accustomed to personalised experiences, whether its Spotify creating a custom playlist, Amazon recommending an associated product, or LinkedIn suggesting a connection that they worked with years ago. Many organisations think that these approaches and the level of complexity needed is beyond their budgets, priorities and skills. Twin this with the fast rate of changing consumer behaviour and the resulting amounts of data to make sense of, and it can be overwhelming.
Technology such as Cortana Intelligence Customer Insights from Microsoft is breaking down any perceived barriers for organisations of many sizes and skillsets to be able to offer demanding customers the services they come to expect.
Whilst the Customer Insights Cortana Intelligence application works seamlessly with Microsoft solutions such as Dynamics 365 (CRM and AX) as well as Office 365, Azure IOT and Bing it also works with third party data sources such as Salesforce, web analytics, marketing automation apps, social media apps etc. Look how easy it is for users to see this data in their daily life:
In this customer scenario below, we see a typical set of connected events that allows a bank to quickly understand that a customer’s ATM availability weren’t suitable for her places of work and home; and be able to proactively act on this by providing additional service suggestions to her via the customer service team and directly to her mobile app.
Customer Insights can do this via bringing together multiple sets of data (geography, social media activity, customer preferences and history), that already exists within the organisation.
Such data, along with insights gained from processing it in pre-built machine learning models and analytics, allows the bank to prioritise her as a customer, match suitable products and send her the offer via her preferred channel.
No matter what your industry, data sets or customer profile, there will be similar scenarios that require such connected events in order for your business to be more competitive.
Speak to Prodware today and schedule a workshop to identify areas in your business where analytics and intelligence can drive transformation.