Artificial Intelligence needs data, and data needs Artificial Intelligence. Almost every business today thrives on data and they require technology (AI mostly) to tame the big data and make sense out of it. However, the output from such AI driven platforms will only be good if the data fed to them is ‘good’ enough.
Data’s primary job is to support brands acquire customers, retain existing customers, and grow revenue. It should also help marketers with useful insights on how to interact with customers more effectively. But how exactly do you know that the data you are using is telling you the right things and is capable to help you achieve your business goals? And how can you use data to engage with your customers effectively?
AI requires quality data and third-party data is just not considered as ‘good’ data. The challenge with third party data is that the source is not known and we do not know how updated it is.
Brands now use technologies like Chatbots, Voice-activated assistants, the Internet-of-things (Smart Fridges, Smoke alarms, entertainment systems etc.) to collect intelligence from their customer which are reliable and very effective in advertising.
The Coca Cola company is a perfect example of a brand which is at the top of the game using such data and intelligence. The brand closely tracks how it’s products are represented across social media and uses algorithms to determine where their customers are, and what situations prompts them to talk about their brand. These data are used efficiently to serve better ads to their customers. Amazing right!
Data actually decays, even though not literally. Someone gets married and changes their name every 12 seconds, more than 6000 people die every hour, 11% of world’s population changes their address every year. This only reinforces the fact that if you are not running regular data health checks then you might be missing on your current and potential customers.
Always verify customer contact information before they reach your customer database. Include automated verification steps while collecting customer data through web forms, CRM field, customer service forms etc.
There are many software tools available for such data health checks. Make that a routine part of marketing operations.
Sync the verified, clean data across systems- using no-code data integration tools, master data or API synchronization.
Brands that create personalized advertisements using their own data has campaign success faster than others who do not. AI driven advertising and marketing automation platforms can help serve personalized ads without any human interference.
The day to day repetitive and mundane marketing tasks can be very well shifted to machines so that marketers are left to do what they can do best. AI marketing tools can process data and identify patterns efficiently to classify customers, recognize customers and even use the data to optimize advertising campaigns. If you are still one of the overworked marketers than you are definitely not using AI to make data driven decisions for you.
There’s never been a better time to adopt AI, if you are a data-driven marketer. Also, it is important to focus on the right data rather than more data.