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Three Tools to Help You Build a Customer-centric Business

When the topic of customer centricity arises, what follows is often a conversation that is more about customer care than customer centricity. The discussion will revolve around customer care representatives, response times, call logging and other items related to customer care. However, customer centricity is an organization-wide, top-to-bottom focus on doing everything possible to make the customer happy. While customer care focuses on a department, customer centricity is a diffuse corporate culture that recruits everyone in the organization to work towards achieving the overarching objective of making and keeping customers happy.

The story of Zappos is perhaps the perfect example of how a small company managed to outmaneuver large retailers like Amazon and Footlocker to succeed in the hyper-competitive online retail shoe market. By embracing customer centricity as an organization-wide culture, Zappos turned an onerous experience (buying shoes) into an enjoyable and streamlined experience. In the process, Zappos earned the trust and love of customers, resulting in such a massive competitive advantage that Amazon, anticipating imminent defeat in the retail online shoe market, ended up buying the company for $1.2 billion. This sale price was not for the inventory Zappos had, or even their technology, but rather, for the massive customer loyalty they had established by being a customer-centric company.

In this article, we highlight three digital transformation tools that can help any company become customer-centric and win the battle for customers’ hearts.

Analytics

The first step to achieving customer centricity is identifying customer needs. For smaller companies, this is not a major challenge as it is possible to measure customer interactions and even run in-person qualitative surveys. For large corporations with thousands of customers interacting with multiple departments, this process becomes complicated. However, there is one thing that large organizations have that can make the process of identifying and quantifying customer needs easier and faster: data. Most large organizations, especially those that have digital interactions with customers, collect mountains of data. The problem usually is that this data is in silos, abstracted, and hardly analyzed.

Big data analytics can turn this data into actionable insights that organizations can harness to help direct their customer centricity efforts. McKinsey found that organizations that manage to extract customer behavioral insights from data routinely outperform their peers, returning 85% in sales growth and 25% in gross margins comparatively. However, organizations must be ready to break down data silos to create a single view of each customer. In this way, data collected in one department can be merged with data generated from multiple other departments to provide a holistic view of customer sentiments. To leverage big data, organizations should start by analyzing existing data to identify critical patterns, increase customer-focused productivity, identify and reward employee customer centricity efforts, and accelerate development of breakthrough solutions centered on customer centricity. Such data analysis would involve first categorizing and cleaning collected data, which would then undergo data modeling mapped onto identified business outcomes. Digital modeling tools such as Tableau, Strata, and Visio would be helpful in this exercise.

Engagement

In an increasingly multi-device, customer-centric marketplace, organizations are facing a deluge of customer interactions from all directions. The average customer today has multiple communication apps on their phone, all of which they may use to reach an organization. Moreover, some of these digital channels may not directly address the organization, such as when a customer hashtag-mentions a business. This explosion in engagement channels has left organizations grappling with how to respond on all these fronts in a seamless, prompt and cost-effective manner. The answer to this challenge lies in developing a culture of customer centricity.

In a hypothetical situation, a customer upset with a purchase angrily tweets, simultaneously @-mentioning the CEO and creating a dilemma for the company: does the CEO ask customer care to respond, or the PR department or respond personally? This dilemma happens all the time. By creating cross-channel data sharing, such an instance would instantly pull in the CEO, legal, PR and customer care to play a role in engaging the disgruntled customer, all while abstracting this process from the customer. By developing integrated and customer-aligned digital listening and interaction channels, organizations can provide faster, better quality and more personalized engagement that engenders customer loyalty while also bolstering brand equity.

Automation

The final piece in the puzzle is automation. With data, an organization can know what a customer needs, and with seamlessly integrated engagement channels, the organization can respond to customers using their preferred channel. Automation takes these two blocks and turns them into a repeatable and scalable formula deployable in multiple diverse scenarios. Automation tools like chatbots and AI-assisted call routing allow an organization to deploy customer centricity at scale through the rapid transformation of customer data into actionable customer-centric tactics. Through automation, employees can focus more on customer-centric tasks and less on rote, repetitive tasks.

Take, for example, Drift, a company that provides automated conversational marketing tools. The company recently launched Drift Intel, a tool that serves up, in real time, contextual data about anonymous prospects agents are chatting with via the Drift chat application. This way, a sales agent has key details like the anonymous prospect’s company, rank at the company and any other public data, enabling them to offer the prospect a better sales experience. By automating this step in the sales process, Drift Intel helps sales agents focus more on customer-centric activities such as providing data-driven solutions and less on traditional sales-related activities like prospect mining. Companies seeking to integrate, and scale customer centricity must be willing to embrace this level of automation.

Conclusion

While overhauling a corporate culture takes time and requires significant political will within the organization, digital transformation affords some shortcuts to a customer-centric destination. By responsibly collecting and analyzing customer data, embracing integrated multi and cross-channel engagement and harnessing automation, organizations can compete more effectively in a market undergoing rapid digital transformation. Neglecting to do so exposes the organization to disruption by digital-first customer-centric startups focused entirely on giving customers the very experiences legacy businesses have been slow to offer.

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