As digital disruption continues its unstoppable march, digital engagement is rapidly evolving and customers’ expectations that they will get what they want during moments of digital interaction continue to grow. Now more than ever, firms need to understand their customers during and across these moments — and use this understanding to surprise, delight, and personalize. To do this, firms and their insights pros need to cultivate digital intelligence (DI), which Forrester defines as:
The practice of developing a holistic understanding of customers across digital touchpoints for the purpose of optimizing and perfecting the experiences delivered and decisions made by brands during moments of engagement.
To build a holistic understanding — and synchronize engagement optimization — across a growing digital customer engagement edge, firms have procured a plethora of DI tech to deliver capabilities such as web analytics, mobile analytics, behavioral targeting (personalization) capabilities, and more. Initially, the tech was procured in isolation by various relevant teams, including those for web, digital, marketing, mobile, and products. But leading practices have reached a tipping point; they are starting to mature their DI strategies to the point of coordinating the adoption and integration of this tech. The result is that the last 18 months have shown a growth in interest and adoption of platformsthat deliver multiple DI capabilities.
Your digital intelligence strategy and implementation is struggling to keep up with your device-hopping customers. You’re trying. And it’s difficult – so many obstacles. But you face the Digital Dilemma, introduced by colleague Nigel Fenwick: your customers’expectations of digital experience keep rising. When any digital experience they have with you doesn’t meet their expectations, their perception of the value your firm provides falls … which leads to risk of customers taking their business elsewhere. Ouch. So, tackle the Digital Dilemma head on. Focus your digital intelligence strategy like a laser on the customer experiences that matter most to your business outcomes. How? With an actionable digital intelligence strategic plan. Here are 3 of the key components your strategic plan must include.
1. Align the plan to the right metrics and KPIs. The optimal approach is to align measurement with customer-focused KPIs that stakeholders are already measured on. Simple, but not necessarily easy. But this is how you get that laser focus on the experiences that matter most to outcomes.
Over the past few months, following publication of my "Customer Insights Center of Excellence" report , there’s been a significant uptick in questions by insights and analytics teams who want to talk to us about CoEs. That’s a positive sign that firms are feeling the crunch to get more value from their insights functions. What’s the evidence for that conclusion? What can we learn from who’s asking about insights CoEs? And most importantly, what really matters in how you organize?
Before we dig in to answers, let’s set the bar on what “great” looks like in truly customer obsessed organizations: they use data for insights to improve customer experience that matters most to business outcomes. As my colleagues James McCormick, Brian Hopkins, and Ted Schadler write in their recent report, "The Insights-Driven Business," customer obsessed businesses act on insights in closed loops, at speed, and at scale in all parts of the firm. They embed analytics and testing directly into operating teams. And, firms who implement these approaches run faster and fleeter than you. The pressure is on from insights-driven organizations.
In Forrester's new report, The Insights-Driven Business, my colleagues Ted Schadler, Brian Hopkins, and I have identified a predator: the insights-driven business. These businesses are vigorously applying insights to decisions and customer engagements at every opportunity. Their leaders have a fundamental and emotional understanding of the value of insights in driving their business today — and for developing its future. They have corporate strategies and cultures that mean that leveraging data, analytics, and insights is easy and deeply embedded in everything they do. For these firms, prioritizing and coordinating investments in data and technology is not a tortuous process of guesstimating ROIs and long procurement cycles.
So who are these predators? Well, there are obvious players like Facebook, Amazon, Google, Uber, and Netflix. But, less obviously, there are many long-standing mature enterprises across many different verticals: Alaska Airlines,The Washington Post, some European football clubs, some retailers, and others that we call out in our new report are successfully transforming into insights-driven businesses today.
The questions below may sound familiar to you. I hear them from leaders of business insights teams of all kinds, from quant to qual, digital analytics to database marketing, customer analytics to voice of customer, market research to competitive intelligence, campaigns to customer service, behaviorial to predictive, B2C to B2B, CPG to pharma – you name it:
"I lead our [name the insights area[s] here] team. We’re struggling to get our business and operational areas to take action on insights – heck, sometimes we don’t even know what happens to the insights we provide. How do we change this?"
"Our insights teams work in silos that have built up over the years. The teams are good at what they do. But how do we pull together and combine our different flavors of insights to get more customer understanding? How should we organize?"
"I've been asked to re-organize [or, I'm new and I've taken over] our insights areas. I need to give a presentation to the C-team about what I'll propose. Any ideas on a framework I should use?"
China Unicom demonstrated its big data analytics platform, including customer analytics, during the Shanghai World Mobile Congress last week. Huawei is helping China Unicom’s Shanghai affiliate build a big data analytics platform that can collect and analyze customer demographics and operational and behavioral data. For instance, it can estimate a consumer’s monthly income based on annual mobile fees, know whether she is walking or driving, and what routes she regularly takes. Such data is unique and even more comprehensive than that generated by Internet service giants like Baidu, Alibaba, or Tencent. China Unicom will begin to leverage this data analytics platform to monetize data in several ways:
Retain customers. China Unicom can predict which high-value customers may be thinking of dropping its services and target marketing based on the customers’ context to retain them. For instance, the system can automatically send a targeted offering when a customer passes by a China Unicom office. In 2014, the telco performed A/B testing among 200,000 Unicom subscribers in Shanghai who were thinking of changing telecom service providers. This helped China Unicom retain RMB 10 million in revenue from those users receiving targeted marketing offerings from the system.
Enhance public security. China Unicom uses the platform to help the Shanghai city government to monitor people’s location in the city in real time. The system provides a real-time heat map and automatically sends an alert when it discovers that too many people are crowded into one area. This can help the government avoid accidents such as the one that occurred in the Waitan district of Shanghai last year.
I attended Huawei’s 2015 global analyst summit in Shenzhen last week and studied its latest strategy for big data innovation. In a change from its previous big data offerings around storage, Huawei has reorganized the data analytics department and focused on infrastructure software that enables big data applications from ISV partners. Mr. Zhu, General Manager of Huawei FusionInsight, talked about FusionInsight, which financial institutions like ICBC and China Merchants Bank use to enhance customer analytics capabilities like customer recognition, segmentation, and marketing automation. Basically, Huawei FusionInsight is a data analytics platform with two major components: 1) a distributed open “database” platform that includes Hadoop, Sparc, and Storm and 2) “middleware” with open APIs to enable multisource data management and analytics.
Chinese financial institutions have a huge amount of legacy transactional data as well as in-motion online and mobile banking data, but they are unable to deal with all of it. With the previous systems of record, financial institutions couldn’t analyze all of this structured and semi-structured data in a unified “data pool.” To solve this problem, they are using Huawei FusionInsight to consolidate multisource data and enable more efficient customer and marketing analytics. Huawei FusionInsight is creating new value in the customer journey for a leading Chinese commercial bank by allowing it to:
Retaining and delighting empowered customers requires continuous, technology-enabled innovation and improved customer insight (CI). The logic is simple in theory, but that doesn’t make it any easier to implement in practice.
In my recent report, entitled “Applying Customer Insight To Your Digital Strategy”, I highlight the top lessons learned from organizations in Asia Pacific (AP) that are successfully leveraging CI to fuel digital initiatives. It all starts by ensuring that data-driven decision-making is central to the digital strategy. With that in mind, I want to use this blog post to focus on two key lessons from the report:
Lesson One: Establish A Clear Mandate To Invest In Customer Analytics
Successful companies serve empowered customers in the way they want to be served, not the way the company wants to serve them. When building a mandate you should:
■ Expect natural tensions between various business stakeholders to arise. To secure buy-in from senior business decision-makers, start by illustrating the clear link between digital capabilities and data as a source of improved customer understanding. Identify measurable objectives and then link them to three to four scenarios that highlight where the biggest opportunities and risks exist. Continue to justify data-related investments by restating these scenarios at regular intervals.
In my last blog post I outlined Forrester’s key customer insights (CI) predictions for 2015. Now I’d like to drill down into some of the key barriers to CI effectiveness we’re seeing among Asia Pacific-based organizations. This content was pulled from my recently published report, which Forrester clients can access here.
Core competencies of effective CI pros have typically centered on customer segmentation and campaign performance measurement. When extending these capabilities to digital marketing strategies, the goal is typically to enable more effective customer acquisition and onboarding by extending reach. In other words, digital innovation often simply means “better campaigns.”
But what happens once that process is complete? It’s not enough to have a world-class digital capability for acquiring new customers. Empowered customers expect the same type of seamless experience, improved efficiency, and heightened responsiveness in all subsequent interactions with your brand.
So why so many firms struggling to realize the full potential of customer analytics to effectively serve and retain their customers? I’ll give you four reasons:
Chinese businesses have been in a state of digital transformation for the past two decades. Since the early 1990s, many enterprises owned by national or local governments have been privatized, and many of those realized that they could make information technology their key competency. However, traditional retail and manufacturing brands in China are very fragmented. The country lacks a local version of Wal-Mart or Macy’s — large organizations that dominate specific sectors.
The rise of Internet companies and their new business models is digitally disrupting already struggling traditional brands. Internet companies in China are using their strong capital resources to take center stage in many markets, creating new service delivery models, bringing online experiences offline, and making transactions through online marketplaces instead of in physical stores.
Most of the traditional brands that I spoke with in the course of the research for my most recent report were unable to react properly, as they were using immature digital intelligence to understand online users. But traditional brands have now realized the value of doing business online and intend to apply advanced digital analytics to understand customer behavior across the multitude of digital channels — web, social, and mobile. For instance, Chinese banks are starting to employ digital analytics to understand how people use Internet financing.One of the four largest Chinese banksis accustomed to analyzing transactional data but has limited experience in online user behavior analysis; to offset this, the bank recently announced a plan to implement web analytics tools to understand how customers interact with its website, search engine, and social platforms.