“The best minds of my generation are thinking about how to make people click ads…that sucks” – Jeff Hammerbacher
When you talk about Digital and Data Science combo, you normally think of the front-office MarTech (marketing technology) – advertising, marketing, sales, commerce, service. This is where most companies are investing as they race to deal with new customer experiences, better engagement, promotion effectiveness and more efficient commerce transactions.
MarTech is about digital and data science platforms that help deepen relationships with customers, simplify and improve customer experience. They aim to increase digital engagement by delivering differentiated experiences.
MarTech is growing partly because the proliferation of “screens” goes well beyond phones, tablets and desktops. There are exciting new developments as “screens” extend to the TV, wrist, in-home automation or car. The pulse of digital experience is speeding up as new technology like 5G, virtual and augmented reality become more feasible and viable.
MarTech is also evolving with data science, analytics, machine learning and AI. By applying intelligence to interactions, promotions and advertising, market leaders are completely changing the “art of the possible”.
Augmented Reality and Virtual Reality, Speech driven interfaces (e.g., Siri, Cortona, Echo/Alexa) all represent catalysts to the next wave of digital marketing innovation.
As a result, the MarTech (marketing technology) landscape grew even bigger . According to Scott Brinker there are as many as 5000 marketing technology solutions — almost twice as many as 2015. We will definitely see an M&A boom as vendor consolidation becomes inevitable.
“Shopping is getting personal/easy/fast. Machine learning is enabling interactions to become more targeted, relevant and intelligent.” Mary Meeker Internet Report 2017
The challenges facing retailers in the midst of this transformation are legion. Traffic at many shopping centers has dwindled, price competition is heating up, and 100+ million Americans are Amazon Prime customers — locking them into a system where they can get free delivery on millions of items and access to exclusive movies, shows and video games.
It doesn’t take genius to predict that digital induced pain for brick-and-mortar retailers is going to get worse. The expectation gap between what consumers are expecting from retailers and what they are receiving is getting wider. Consumers are spreading their buying activity across channels, forcing retailers to spread out their digital investments. This puts significant stress on execution, product/platform management, design and leadership.
Evidence of this value migration from physical to digital is mounting every day. Against that backdrop, Wal-Mart is closing over 269 stores as it retools portfolio. [Walmart paid more than $3 billion for Jet to speed its data driven digital transformation. It’s been acquiring smaller players like ModCloth, Moosejaw and Bonobos to appeal to Gen Y and Gen Z segments.] Macy’s said that it will shutter over 36 stores as store traffic declines faster than expected, and Finish Line said that it would close 150 stores by 2020. Gap, J.Crew, American Apparel, Sears and Kmart, Target, Nordstrom are all facing similar headwinds.
Data drives digital transformation.
Starbucks CEO Howard Schultz laid out his thoughts on the future of retail, “three years ago we began to envision that there would be a seismic change in consumer behavior, and that seismic change was due in large part to e-commerce, search and smartphone shopping.”
It’s fascinating to watch retailers experiment and shift tech/platform strategies to deal with digital disintermediation, showrooming, physical-to-digital channel integration, mobile shoppers, same-day delivery/fulfillment, programmatic targeting, online native models and now the new buzz.. AI and augmented reality.
While most retailers seems to know what to do….they are unable to execute consistently or effectively around more efficient search, pricing, targeting or data mining. A talent gap in many cases. A platform gap in others. Others are hindered by legacy IT apps and infrastructure. Others by silos of data or necessary next generation technology capabilities like A/B testing, data science and machine learning.
This data driven digital retail UX and shopper evolution is a continuation of the trend from 1960s.
Analog to data-driven digital transformation
For the times they are a-changin’… Bob Dylan
Customer channel behavior and interaction model is evolving constantly. Just when retailers, banks and others think they have multi-channel figured out the channel/interaction game is shifting with chatbots, virtual assistants, speech shopping, and other innovation.
New technologies have emerged to
revolutionize the way end-users
interact with technology and to
reshape businesses. According to Gartner: “Conversational AI-first will supersede cloud-first, mobile-first as the most important, high-level imperative for the next 10 years.”
Basically, customers are not interacting with brands in a linear fashion… they are jumping around from channel to channel and expecting the experience to be seamless and relevant.
For instance, in online shopping, women are more likely than men to reach for their smartphones and tablets to research and make purchases. Of U.S consumers who say they’ve completed a purchase on a mobile device in the last month, 66.5% are women and 33.5% are men. Compare that to 2013, when a greater share of men than women completed purchases on mobile. [BusinessInsider, The e-commerce demographic report].
To better understand, customize and respond based on customer behavior/context/clicks, Fortune 500 companies are making large investments around Programmatic Marketing (“Marketing that learns”). Specifically, the objectives are:
- Visualize and map the 1:1 customer journey by personas.. Customer journeys are an illustration or visual representation of all points of interaction across touchpoints.
- Optimizing on the right journey attributes to increase yields by >30% lift… Uncover the right combination of web, mobile and physical channels, content and experiences that best achieves the target goals
- Enable marketers to identify journey bottlenecks for individuals and aggregates
- Leverage actual behavior data to enhance and personalize the experience for each individual customer
One of most often implemented use case in Programmatic Marketing is customer journey mapping and analytics. Why? Because, deciphering the nuts-and-bolts” of individual customer journeys (and deducing intent) is core to improving customer experience and driving brand loyalty.
Salesforce CEO Marc Benioff said at a recent conference: This is a huge shift going forward, which is that everybody wants systems that are smarter, everybody wants systems that are more predictive, everybody wants everything scored, everybody wants to understand what’s the next best offer, next best opportunity, how to make things a little bit more efficient.
The retail store that does not have a meaningful relationships with the consumer is dead or going to be dead.
But meaningful relationship are easy to engineer. Today’s marketer is faced with an almost impossible task: Create relevant, individualized journeys for a customer whose channel preferences, purchase behaviors, and tastes evolve with unmatchable speed.
The cutting edge in data-driven digital and mobile marketing is “marketing in the moment”, which is the ability to identify and optimize precise moments of marketing influence across multiple channels and devices. In digital advertising, firms like Facebook and RocketFuel are using continuous scoring algorithms that score each moment to predict whether an individual will react favorably to an ad shown (display ads, search, social media and video) at a given time.
So how do marketers (and advertisers) understand what their audience wants or will see as valuable? That’s where data science comes in. When you strip away the rhetoric, data science is just about finding meaningful insights through analyzing large datasets.
Data Science is increasingly fueling data-driven digital marketing strategies at cutting edge firms…. Marketing learns, acts, and evolves across the consumer journey. Programmatic real-time bidding platforms is growing to dominate ad spending.
“Marketing and Advertising That Learns” Strategies
With digital, value is migrating from outmoded business models to new business designs that are better able to satisfy customers’ priorities.
As digital permeates every nook of business, firms will need diverse set of digital leadership. CIOs who step up to a digital leadership role can expect to contribute in a number of valuable ways, perhaps even assuming the über digital role with responsibility for all things digital. Those who can’t will be relegated to play subordinates to the emerging roles of Chief Digital, Data and Analytics Officer, or to the CMO, CFO, or COO, their portfolio limited to the infrastructure and corporate systems.
People have transformed how they consume information, research products and services, make purchasing decisions and share their views and experiences.
So in every boardroom, the buzzwords are flying – omni-channel, mobile-first, digital engagement, AI-first, digital transformation, Conversational AI, multi-screen engagement, millennial marketing, digital operating models, and so on.
Every leader has a semi-clear idea of what the digital strategy needs to be (Increase digital innovation; Improve customer experience by providing access through preferred channels; and drive cost efficiencies) — but there is very little clarity/consensus in terms of how to crisply translate the digital strategy into a next gen engagement architecture and create tangible ROI.
In other words, there is a growing “knowing–doing” gap emerging.
“i don’t think retail is dead. Mediocre retail experiences are dead.” Neil Blumenthal, CEO @ Warby Parker
“In e-commerce, lines are blurring fast across Ads/Content/Products/Transactions.” Mary Meeker, Internet Report, 2017
Seismic shifts are putting customers in control. New innovations like mobile Augmented Reality (AR), Conversational-AI are changing the landscape of what’s possible in terms of consumer experience. This is truly an exciting time to be in marketing technology (MarTech) and data-driven marketing. Lot of innovation, experimentation and chaos.
Marketing technology (MarTech) is composed of the following: data, analytics, sales and marketing automation, email, predictive tools, commerce technology, shopper marketing and payments.
Why this tremendous growth in Martech? The customer lifecycle around acquisition, engagement, commerce and retention is going through a major upheaval. Changing buyer behaviors forced companies to change how they market and sell. Instead of the classic CRM and “inside-out” approaches, a new wave of “outside-in” fresh rethinking around engagement, experience and micro-targeting is taking place.
Chief marketing officers are already outspending CIOs on tech as they race to bring marketing to the B2C and B2B digital world. According to Gartner’s CMO Spend Survey, marketing budgets remain steady at >10% of company revenue. However, the growth and investments are all in digital marketing space as firms focus on millennials, online customer experience, micro-targeting and multi-channel engagement.
Marketing technology budgets appear to be growing faster for revenue-related capabilities than more internal efficiency improvements. Also cutting-edge marketing technology is becoming legacy quickly. The effectiveness of the generation #1 digital marketing playbook is eroding with mobile-centric usage patterns, ad blockers, and spam filters. Consumers are now empowered with new and better control over interruptions from marketers. Buying lists, blasting emails, and cold-calling were no longer effective.
A new digital engagement playbook enabled by next generation martech is needed.
Good -> Great… Marketing Technology Architecture
As the race to become digital and engage prospects/customers gains momentum in every industry, CMOs are faced with an interesting challenge they never had to deal with before:
- What is an efficient and effective digital architecture?
- What does a “good” architecture look like?
- What does world-class mean with respect to sales, marketing, service and commerce technology?
- What is an effective mobile engagement architecture? What is the best way to systematically approach Mobile Onboarding, Activation and Retention (MOAR)?
- How to make investments that align with a strategic customer engagement plan and not a tactical “plug-the-hole” gap fillers? Read more
Mobile is rapidly expanding opportunities to engage customers and increase stickiness. There is incredible amount of innovation taking place around Mobile Engagement, Messaging and Notification platforms. Messaging + Notifications = New mobile engagement toolsets. New capabilities are emerging to: power push notifications, sophisticated audience targeting, message centers, digital wallet programs, and location analytics.
Notifications are growing rapidly and becoming increasingly interactive. This is driving new touchpoints with messaging platforms and other apps.
Source: Mary Meeker, Internet Trends 2015
Wearables are increasingly become a central part of mobile engagement enabled by push notification strategies. Many retailers, CPG firms are experimenting with new micro-targeted contextual experiences leveraging proximity beacons, push messaging to integrate coupons, recommendations and next best offers into the watch apps to monetize push and in-app messaging.
The Apple Watch, for instance, is a long-term megatrend that we believe will transform user engagement via notifications and alerts. Unlike the tablet, phone or desktop, wearables, like Apple Watch, are built for quick interactions e.g., notifications and alerts.
A study by Kleiner Perkins found the average user checks their phone over 150+ times per day (Facebook, Twitter, WhatsApp etc.).In its 2014 annual Internet Trends report, KPCB found that people check their phones, on average, 23 times a day for messaging, 22 times for voice calls, multiple times to see if there are Facebook updates and 18 times to get the time. We expect many of these 150+ “interrupts” are naturally going to migrate to the Apple Watch.
The Apple Watch’s small screen size enables a fundamentally new user interface (UI) and user experience (UX). There are new inputs (force as well as touch), subtle vibration, digital “crown” control, new inter-device communication modes, and new data points that phones have never been able to collect (e.g. heartbeat).