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How CDOs & CIOs are Driving Digital Transformation

Ajay Khanna, VP of Marketing, Reltio

I recently got an opportunity to present at MITCDOIQ Symposium in Cambridge, MA. Here is the outline of my presentation where I discussed how today’s CIOs and CDOs are driving digital transformation across their enterprises. It discusses the key drivers for digital transformation and how Modern Data Management is helping them with their initiatives. You can now download my slides from the event from this page.

Today’s business landscape more dynamic than ever. New revenue models, stringent regulations and high customer expectations are forcing organizations to evolve or face being overrun by more nimble competitors.

CDOs and CIOs of established business are looking to digital transformation as a key initiative. But what exactly does digital transformation entail? At its core, any digital transformation requires clean and consistent data, reconciled across systems and channels. An enterprise-wide data management foundation that ensures real-time access to reliable data of all types at scale and is non-negotiable. Data access must be democratized across all groups and divisions so that teams can get a 360-degree view of customers, products, organizations and more.

However, it’s not just about disconnected siloed analytics. It’s about the next generation of operational data-driven applications that allow frontline business users to gain relevant insight and intelligent recommended actions so they can achieve their goals. This session explores how some of the largest companies in the world are transforming themselves using the same modern data management technology used by Internet giants such as Amazon, Facebook, LinkedIn and Google.

The presentation covers the following topics:

  • Changes in business environment and need for agility

  • Digital transformation drivers

  • Digital transformation examples

  • Data-driven digital transformation with Modern Data Management

Please fill out the form below to download the presentation slides:

Is it About the Groceries or the Data? How Whole Foods Tried to Avoid Being Amazoned

Ramon Chen, Chief Product Officer, Reltio

Amazon announced that it is acquiring Whole Foods for $13.7B.  There are several theories going around about the move, from direct competition with Walmart, to an interesting theory by Blockchain Expert Richie Etwaru, who ties in Amazon’s designs on becoming a pharmacy with the deal, and whether they might go after a healthcare payer next. Some even are speculating that Nordstrom is next on the Amazon shopping list.

As the Chief Product Officer at Reltio, my focus is on the data, and helping companies avoid being “Amazoned” (Informal definition: Brick and mortar stores under threat from online competitors). Rewind 1.5 years ago, an article by Phil Wainewright of Diginomica caught my attention. “Whole Foods Market teams with Infor to transform retail.” Credit Whole Foods executive vice president and CIO Jason Buechel with his vision to be more data-driven, and to create one source of the truth.

Based on what we know about customer behavior, attitudes we know about that store and region, we want to make decisions on everything from assortment planning to space allocation, pricing, promotion. A lot of that has got to do with insights from the platform and having better analytics to make decisions.

 

Whole Foods and Infor’s partnership was supposed to result in a next generation, cloud-based retail management system to transform its core operations. Infor, which hosts the software on Amazon Web Services (AWS), intended to make the capability available other retailers in the industry.

In the article, Buechel also told author Phil Wainewright of Diginomica that Whole Foods has carefully weighed the pros and cons of that cloud infrastructure being operated by Amazon Web Services (AWS), which is part of a company with which it competes in the online grocery market.

We’re OK with this decision, for two reasons. One, the ‘chinese wall’ — the commercial commitment that Amazon does not have access to the data or any of the things that are really being processed within AWS within this solution. We’ve had specific direct conversations with Amazon involving our legal teams and really understanding that limitation.”

If Amazon were ever to breach those commitments I think it would be devastating to their business — and a quite profitable business for them as well.

There’s also the huge consideration that this is the largest, best and most cost-effective platform in this space. Another partner would not yield as good a result. It is not just cloud hosting, it is a platform, a toolset, that allows speed-to-market that are not offered by other providers.

Kudos to Phil Wainewright for this article, because it called out what all Retailers are thinking today. The only way to avoid being “Amazoned” is to run on the very platform, Amazon Web Services (AWS), that can allow me to compete with Amazon.

Retailing executives are asking themselves am I okay with that? What are my alternatives? Clearly Whole Foods CIO Jason Buechel knew it was a risk worth taking. He may not have foreseen that Amazon would acquire Whole Foods, but he definitely knew that doing nothing was not acceptable.

Other data experts saw this coming as well. Bill Schmarzo, CTO, Dell EMC Services (aka “Dean of Big Data”) posted an amazingly relevant digital transformation blog post, with a Grocery chain case study less than a week ago!

As for the question, did Amazon buy Whole Foods for the groceries or the data? Clearly this is an amazing twofer. They get a physical presence that can help their delivery and Amazon Fresh efforts, but they also get the significant dataset of customers who buy groceries from Whole Foods. They now have the information to bring together a complete single view of the customer, from brick and mortar shopping to online purchases. 

In the end, the data-driven takeaway to all retailers is not just evolve or be Amazoned, but do it fast because no company can afford to spend years working on digital transformation, when their very survival depends on better customer experience, better marketing, better omnichannel engagement, personalization and more.

At Reltio, we’ve honed our Modern Data Management Platform as a Service (PaaS) to give companies the agility they need to not just survive, but thrive. Incidentally, Ajay Khanna, Reltio’s VP of Marketing will be presenting on this exact topic at the MITCDOIQ Symposium in Cambridge, MA on July 13th. We hope to see you there.

Turning Customer Data into Actionable Insights

Ajay Khanna, VP of Marketing, Reltio

This week I got an opportunity to present at DBTA’s 2017 Data Summit conference. The topic of my discussion was “Turning the Customer Data into Actionable Insights.” All enterprises want to understand their customers better so they can engage the right customer, at the right time, with the right offer, via the customer’s preferred channel. The objective seems simple, but is quite hard to deliver if you do not have access to reliable data. Large volumes of data are being collected, but the data is scattered across multiple systems. There is no single source of truth across functional groups like sales, marketing and support. Different channels have their own version of the truth. Therefore, the customer experience remains disconnected, and customer insights are quite shallow.

The presentation covered how we can get to personalization at scale using Modern Data Management. The following aspects were covered:

Establishing a Reliable Data Foundation

To Make this experience more connected, we must bring the customer data together and then use that data for meaningful consumer insights and intelligent recommendations.
Start with connecting to all required data sources – internal systems (CRM/Marketing Automation etc.), external systems, social streams if needed as well, and enrich it with third-party data subscriptions as needed. Match, merge and clean the data to create a single, reliable source of truth of your customer profiles. Modern Data Management lets you identify potential matches and overlaps of the profiles. It helps to compare and contrast similar profiles and then automatically consolidate to create operational values using survivorship rules.

Please fill out the form below to download the presentation slides:

Uncovering and Understanding Relationships

The next important step is to reveal the relationships between the data entities. This where the graph technology helps us understand relationships – with a Commercial Graph (similar to LinkedIn or Facebook) you can relate customer profiles with products, accounts, family members and locations. You can establish many-to-many relationships between these data entities to understand where customers shop, what the products of interest are and who can influence their decisions. Uncovering relationships using graph technology helps you with identity resolution, finding influencers in the customer segment, or group individuals into a household and develop targeted campaigns. For B2B customers, you want to see the organizations and business units connected to it, key stakeholders and users of your products, or even contracts associated with various entities.

Single Source of Reliable Consumer Data for Operations and Analytics

Once you have the reliable data foundation, you can provision the data to all customer applications and channels for the connected experience. Moreover, you can provide the data to analytics systems to gain deeper insights about:

  1. Relationships: Modern Data Management lets you utilize predictive analytics and machine learning to guide users and provide intelligent recommendations, based on data and behavior. It helps with identity resolution, can suggest your new relationships and identify influencers (like LinkedIn.)

  2. Next-best-action: Recommendations like the next best offer to send to a customer, at the right time, using their preferred channel and identifying the key influencer to contact in an account and what to offer.

  3. Data quality: Recommendations to improve data quality by suggesting better matching rules, finding potential matches as you onboard new data sources and determining profiles with poor data quality and wrong addresses.

With Reliable Data, Relevant Insights and Recommended Actions enabled by Modern Data Management, we can understand the customer better and provide more connected experiences.

Driving Digital Transformation Through Modern Master Data Management

Ankur Gupta, Sr. Product Marketing Manager, Reltio

Digital Strategy is not a separate strategy, but instead a new lens on the overall business strategy that incorporates customer intelligence, sales & service optimization and digital marketing efforts (e.g. mobile, e-commerce and social). Key drivers of digital transformation among B2C organizations are profitability, customer satisfaction and increased speed to market. Whether you are a retailer, restaurant, travel company, media & entertainment company, lifestyle brand, or a consumer bank, you want to create a seamless, personalized and consistent customer experience across all channels (web, email, phone, stores) and departments (marketing, sales, support).

However, personalization is a double-edged sword. All digital transformation and personalization efforts would fail if data underneath is of poor quality, siloed and delayed. According to an estimate, poor customer experiences result in an estimated $83 billion loss by U.S. enterprises each year because of defections and abandoned purchases. On the contrary, if done correctly, it can considerably boost your business (Amazon’s conversion to sales of on-site recommendations could be as high as 60%). Some of the top of mind issues discussed during various sessions included:

Garbage in – garbage out. 

Today, hyper-personalization is possible because of digital transformation enabled by cloud, mobile, big data, internet of things and many more cutting-edge technologies. Similarly, companies have invented great processes (order-to-cash, supply chain management, onboarding, provisioning) to manage customers, prospects, suppliers and partners. What’s still not treated as a top priority is the quality of data driving these processes.

Omnichannel initiative of any consumer brand is as good as its underlying data. A reliable data foundation alone, created through a Modern Data Management Platform, can lead to a truly personalized engagement,” said Ramon Chen, Chief Marketing Officer of Reltio, during the panel discussion, “Lessons from Lifestyle Brands: Omnichannel Marketing and Strategy.

The thought was echoed by other participants who discussed how reliable data is the key to effective customer experiences.

Data silos within the organization.

Being able to understand and monitor end-to-end consumer journey is vital. Yet, it is not uncommon for each team or function within an organization to define and measure customer experiences independently, in isolation. The result is disconnected global operations, fragmented multichannel visibility and incomplete views of customers that slow down all digital transformation efforts. Data-driven applications built on a Modern Data Management platform gives you not only the 360-degree view of your customers, products, channel partners, or suppliers but also a contextualized view of relationships among these entities. More importantly, it helps you create a single-source of truth across sales, marketing and support to provide the right customer with the right offering at the right time, thus enhancing the customer experience.

Data silos across organizations.

Co-innovation, co-creation and collaborative curation of consumer information, at a big data scale, can open the door to new possibilities. For example, personalized recommendations for food, movies, hotels and shopping can be packaged together for a particular consumer if the companies in these different industries are willing to share data with each other. Furthermore, such data exchange helps these non-competing business entities to monetize their precious consumer data assets. As digital touchpoints proliferation continues, a Modern Data Management solution will help companies to trade reliable data currency in a secure fashion.

Business outcomes don’t feed the underlying master data.

There are no mistakes, only lessons. It is critical to get smarter with each interaction. A Modern Data Management Platform coupled with Machine Learning enables contextual information and helps you answer high-impact business questions such as – Will my customer buy this product or not? Is this review written by a customer or a robot? Which category of products is most interesting to this customer? And so on. On top of that, a Modern Data Management solution captures all actual business outcomes and enriches the master data in a closed-loop, thus continuously fueling the recommendation engine for making smarter predictions.

It’s time for data to be managed in such a way to make true digital transformation happen. Once Modern Data Management is in place, a consumer brand can reap substantial benefits on a continual basis. Starting with proper data quality and alignment of key data assets across systems, departments and channels, it helps build a reliable data foundation for all your digital transformation initiatives. Businesses who will timely address this challenge will be ahead of the competition.