As 2019 gets underway and your marketing plan unfolds, you’ve probably set some goals for the coming year:
We’re going to break down the data silos that keep us from understanding our customers.
We’re going to improve our messaging relevance.
We’re going to target customers more accurately on their preferred channels
Sound familiar? What if you could just find the time to make any one of these resolutions a reality?
Although the promise of one-to-one marketing has been around for many years, brands still send customers too many marketing messages that are irrelevant, generic or only slightly personalized. The problem is that marketers today have too much data and not enough creative time to respond to soaring customer expectations for a personalized buying experience.
Enter artificial intelligence (AI) and machine learning-based marketing tools that are changing the nature of how marketers make decisions and deploy campaigns. For example, an AI-powered marketing assistant can help you quickly analyze campaign performance with simple verbal commands. An automated content management system can tag images, allowing you to easily create better content for your campaigns. An AI-powered software enables you to see what your customers are doing along every stage of their journey. The list goes on.
Machine-driven innovations save time and enable marketers to be creative strategists again, rather than spreadsheet jockeys. The result is that you can course-correct campaigns faster than ever, ending underperforming campaigns sooner and executing new ones that are more personalized and perform better.
Let’s take a closer look at how AI streamlines marketing processes across the customer journey and helps marketers work smarter.
Unified data across all channels
Marketers continue to be inundated with all types of data – from third-party demographics to real-time behavioral data. The challenge is making the data unified, actionable and effective when it often resides in department silos and is spread across too many systems and platforms. You spend so much time tracking it all down that you’re left with no time to make sense of it, let alone act on it.
Like many leading retailers, HSN (Home Shopping Network) relied on separate processes and systems to drive its marketing strategy for each channel. However, this approach made it complex and time-consuming to integrate data on customer interactions across different channels. It was difficult for the brand’s marketers to know which products would appeal to which customers or what kind of messages would inspire them to make purchases. To break out of its channel-by-channel mentality, HSN worked with Watson Marketing to develop an AI-driven marketing platform that would integrate data across all of its channels, including online, mobile, email and direct mail.
The goal was to use AI to create a ‘boundaryless’ experience for its customers. This new approach enabled the company to build a more complete and accurate picture of individual customer preferences based on all of their brand interactions. HSN marketing teams now craft omnichannel, multi-wave campaigns that reach customers on their favored touch points at the right times.
Consumers expect personalized brand experiences, and 94 percent of companies agree that personalization is critical to their current and future success. Yet a common obstacle to deeper personalization is the ability to create multiple versions of content and determine the right combinations at the right time for thousands or millions of customers.
Growing numbers of AI-based systems can process marketing rules and directions and then create and deliver individualized content on the fly to each customer. This hyper-personalization is increasingly based on the predicted behavior of the individual rather than conforming to a statically defined segment. AI makes personalization easier for marketers by learning through each interaction and delivering the right content in the context of the customer’s previous interactions with the brand. When you know how your customers engage with your brand, it becomes much easier – and more effective – to deliver the right message at the right time.
The Georgia Aquarium sought to harness the growing popularity of digital channels to send more personalized communications to its visitors. The nonprofit’s marketers knew that increasing numbers of guests were using their smartphones and tablets to connect with the organization before, during and after their visits. But because data was stored in siloed systems, it was difficult to build a 360-degree view of guest interests and preferences.
The solution was to deploy an AI-based centralized marketing platform based on IBM Watson Campaign Automation, which would house a comprehensive range of customer data, including first names, ZIP codes, visit histories and memberships. Machine learning enabled the marketing team to segment audiences into distinct personas, such as non-purchasers, non-members, members and donors, and to execute highly personalized campaigns that were more relevant to each member of its audience. The result has been an 89 percent increase in email open rates and a 288 percent increase in engagement with those messages. More importantly, the Georgia Aquarium has experienced a 21 percent increase in revenues attributed to the digital channel.
It’s all about the [customer] journey
In fact, customers want the quickest and most intuitive path to get to what they need. As a marketer, you want to provide a better path to customer purchases and satisfaction. Seems simple, right? But as we all know, it’s not. AI can help you analyze the entire customer journey across multiple touch points, pinpointing and alerting you to friction spots so you can diagnose the issues and fix them before they affect your bottom line.
Airlines Reporting Corp. (ARC) is the leading supplier of air travel intelligence and commerce services in the U.S. The company’s martech stack included several best-of-breed platforms, but no straightforward way of connecting them to form a coherent view of individual customer journeys. ARC marketers wanted to better understand what was happening during each step of the customer journey, for example, if customers were having trouble navigating the site, finding information or signing up for services.
The company implemented IBM’s Universal Behavior Exchange to translate customer data from multiple source systems into a shared language, and combine it into a single view of the customer journey. The data is then passed into the Watson Customer Experience Analytics platform, which uses AI to automatically map out customer journeys from beginning to end — even when customers jump back and forth between channels. This approach has allowed ARC to create a rich view of customer interactions across all channels and eliminate blind spots when it comes to understanding the customer journey. Its marketers have already discovered that customers are browsing on tablet devices far more than they knew, which has led them to prioritize experience improvements on the mobile channel.
AI-powered marketing = Smart marketing in 2019
You know what you want to achieve in your marketing, you just need the time to do it. With AI, you can work smarter, and gain a holistic, real-time view of your customers and their relevant interactions throughout the entire journey. AI lets you act quickly on your data and makes it easier to focus on higher value work. Being able to get fast, actionable insights will give your team the time to focus on strategy and drive business results.