Mobile customers are by and large changing the game for marketing and customer experience. With instant access to information, consumers are redrawing journey maps as they find new places and resources to make decisions about their next purchases.
They’re not looking for advertisements, messages, brandspeak or sales pitches. They’re looking for trustable insights, useful, personalized and succinct content and guidance toward an efficient path to their desired outcome. And for most consumers, they want it all on their mobile devices, on-demand.
Brands however, are still serving consumers as if it was still 1999.
When the web was brand new, customer empowerment wasn’t yet mainstream. Even though brands were thrust into a digital realm, they still relied on traditional touch points to service consumers. As they migrated to digital, they did so while learning the art and science of ecommerce.
Fast forward 20 years, and we’re now racing toward a mobile-first and mobile-only web while many incumbent brands are still learning the balance between commerce and e-commerce.
Mobile is a different beast, not just because of the technology and mindset involved, but because of the effects on consumer behaviors, preferences and expectations.
In an era of mobile commerce, connected consumers have learned to seek in-the-moment assistive experiences. This sets the stage for something much more than e-commerce and mobile commerce.
Consumers are giving rise to a new genre of adviser brands that will compete by delivering real-time value and utility against precise expectations and behavior. But, they can’t don’t it without some help.
Progressive experiments with AI and machine learning combined with modern, customer-centered campaigns, deliver notably better results, help strengthen skill sets and raise performance standards that set the benchmark for other groups to follow. Why?
Because they’re centered on adding value to customer experiences based on what people seek, what they value, and how to move them to the next step. Even if marketers aren’t fully versed or in tune with these trends, technology can, ironically, help customer engagement become more human.
I was encouraged by a recent interview I read between Matt Lawson Director of Marketing, Performance Ads at Google and Elizabeth Spaulding, Partner and Global Head of Digital, Bain & Company over at Think With Google. In their conversation, they outline what could serve as a modern construct for AI marketing innovation.
As Spaulding explained, “Marketing technology is continuously advancing, and now with AI and machine learning, companies large and small are constantly rethinking the ways they operate.”
At the heart of this renaissance, are connected, mobile customers who are demanding more personal, relevant, and useful engagement. This gives way to what Google calls “the age of assistance.” It signifies an intelligent genre of customer engagement where brands must shift from marketing-centric, omni-channel campaigns to customer-centric, cross-channel engagement that’s assistive, useful and additive in nature.
For example, when a consumer reaches for their mobile device to start or continue their journey, they don’t want to see retargeting or generic value propositions or marketing messages. They’re expecting brands to know them and deliver content or steps that guide them along their journey in ways that are intuitive and personal.
In the last decade, the advancement of consumer-facing disruptive technologies have been profound. Mobile devices, social media, on demand services and apps, have forever changed consumer behaviors, preferences and values. They’re now curious, demanding and impatient. They expect more from brands to cater to their needs and lifestyle and aren’t going backward.
Now, customers want marketing to stop marketing at them and instead understand and guide them. They demand personalization. They value assistive engagement and useful content and click paths based on context, intent and efficiency.
Studying digital behaviors and investing in AI/machine learning represent substantial opportunities for marketers and businesses to not only modernize marketing, but also do so by adding value to customer experiences in the moments and ways that matter to them.
AI and machine learning are accelerating business transformation by driving new needs and capabilities and as a result, modern expertise. In fact, it’s allowing marketers to upgrade traditional marketing to emphasize precision and performance to reach the right user in the right moment on the right device with the right message.
More so, AI marketing is expanding marketing’s role into CX and customer journey efforts by intelligently offering the next best action (NBA), a customer-focused design strategy that considers the different actions that can be taken for a specific customer to help them take the path that’s right for them.
Spaulding shared why this is the time for AI-powered assistive marketing, “Consumers navigate across multiple channels, platforms, and media, and they’re leaving behind millions of signals about their intent, context, and identity.” She continued, “The problems marketers aim to solve and the data they are dealing with are complex. Machine learning is an effective approach to process all of that complexity at scale and surface the insights that matter to marketers.”
AI is driving marketers to modernize perspectives and skill sets. At the same time, it’s altering the dynamics of marketing departments to connect modern data inputs, machine learning, insights and strategy. Some of the most progressive organizations are building data science teams who can apply big data, via machine learning, to solve more than marketing, but also business problems. Bain research shows that leading companies are 3.2X more likely to have the right analytics talent embedded in marketing.
Wayfair, for example, has different marketing technology objectives supported by different analytics teams. Its direct response team, that focuses on acquisition and remarketing, and its brand team, have dedicated analytics and data science resources, as well as marketing engineering support. This allows them to quickly test, learn and iterate and then shift focus to new projects.
Spaulding referenced Domino’s technology investments as an example of marketing and data-led business transformation, “They’ve grown their workforce to include data scientists and engineers who collaborate with marketing to push the envelope in customer experiences.”
The age of assistance is upon us and it’s just getting started. Customers are sharing via their digital footprints, their intent and what it takes to help them. Processing and executing data at scale is difficult, if not impossible to manage. AI and machine learning represent keys to converting customer behaviors and expectations into assistive experiences. It’s what marketers do to understand what it means to be assistive and the technology they use to do so that counts for everything now.
As Google and Bain point out, successful organizations start with business objectives that are supported with a robust data strategy. “It gives the marketing team the experience and runway to build new muscle in the organization.” Spaulding shared.
While AI/machine learning may sound like the future for today’s marketers, the reality is, that it’s here today. And the irony is, that intelligent machines are here to help you humanize marketing and make it more personal as mobile consumer demands and expectations advance.
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