People sometimes think of artificial intelligence (AI) as the natural language processing they saw in HAL 9000 in the film 2001: A Space Odyssey, or the chess-playing computer Deep Blue that beat Garry Kasparov in 1997. Others see AI as synthetic human intelligence engineered into a friendly voice interface and software, like Apple’s Siri.
By contrast, in the enterprise environment, AI for customer marketing offers a far more practical, personal, immediate, and business-oriented application.
Effective customer marketing is about analyzing billions of signals and automating analytics on a bottom-up basis. It results in highly personal marketing, pairing the right product and offer at the right time to a defined group of people. Questions about individual and group behavior abound. “Like” for those irritating Millennials, what offer would induce a first-time purchase and which product would be ideal as a complimentary purchase? How many and which products are clustered into a typical purchase? How do you scale sales while the company is in a sales plateau? Among a large group of customers, which products and price points match, and which two marketing vehicles are the best to use to reach them? Answering these questions effectively, and in a timely fashion, is key to highly-effective, personalized marketing.
Historically, customer marketing has relied on the organization’s IT and analytics team as the key go-between for data, algorithms, technology and support to answer these vexing questions. However, finding the appropriate customer data for analytics across 100s of unique data sources – both inside and outside the enterprise – and then bringing them together, unifying, cleansing, and enriching the data has proven to be a time-consuming, challenging, manual task. As a result, most companies end up using only a fraction – 10% to 15% by many accounts — of all customer data, that often takes weeks to curate.
Today, artificial intelligence in customer marketing means fixing customer analytics first: all the way from gathering both intent and behavioral data from current customers and/or prospects across numerous sources, doing data preparation, and then applying finely crafted and fine-tuned machine learning algorithms and statistical, mathematical, and other techniques that automatically learn iteratively as data and circumstances change and evolve. This enables marketers to far more effectively retain and monetize their customers.
This is where Zylotech comes in. The company & team has years of solid experience, and success, working with AI in customer marketing. Zylotech’s clients use its two-layered AI-platform to make decisions after making sense of all the customer data at their disposal to enable dynamic segmentation and propensity – all in near real-time.
This is a pragmatic use of AI in a key area where data is produced daily, at tsunami levels. Marketers must react quickly and there is no room for guessing, while the traditional predictive analytics is slow, manual, incomplete and inaccurate.
If you want to learn more about AI and customer marketing, contact ZyloTech for more information.