Data integration and best practices in the age of the digital customer

Nada-headshotBy Nada daVeiga

Organizations are competing more than ever based on how they engage with customers. It’s become a vital part of the enterprise digital transformation agenda. Yet in the rush, integration, a foundational element, is often overlooked in the haste to deploy new digital customer applications and experiences. McKinsey recently observed that “Integrating new processes with legacy systems in a cost-efficient way is a challenge most companies face when they digitize their customer. [1]

Why does it matter, and why is it such a big obstacle anyway?

The problem is that a lack of integration can quickly become transparent to customers. In retail, lack of strong integration between an e-commerce system and the CRM or ERP can result in website ordering, pricing, or shopping cart issues that aren’t visible to customer service. This lack of integration often results in customer frustration or a lost sale. In B2B, poor integration between the CRM and ERP can also lead to incorrectly rekeyed customer or order information, resulting in downstream invoicing issues.

But why is it so hard to pull together more integrated customer processes? Because there are just so many applications within the enterprise that manage a part of the customer process.

For example, a recent study by Ventana Research on customer analytics found that 40 percent of respondents worked with 14 different types of data across at least 6 different systems to derive customer insight. [2]

Five key strategies to connect and elevate your customer experience

With integration being the biggest barrier, let’s look at five strategies key to connecting and elevating the customer experience.

  1. Start with analytics, grow to experience

Why this sequencing? Simply, we have to start somewhere in order to measure key metrics, since only things measured can be improved. Getting a clear 360-degree view of the customer – with metrics around customer satisfaction, engagement, churn, and acquisition – provides the blueprint for targeting the best opportunities to upgrade customer experience.

  1. Put customer experts in control

Who better than the sales or service team to put themselves in the customer’s shoes? Often analytics projects can quickly become an IT-led project. While IT has an incredibly important role to play, in governance and ensuring the efficient use of technology, experts in the lines of business should be enabled to connect the dots themselves.

  1. Customer experience is a team sport – get collaborative

The chances are one of your customer process steps will likely depend on another team’s app. Or the data needed for your analytics project will be within another team’s control. With so much cross-departmental integration, ensure different teams are using the same integration platform to maximize reuse.

  1. Plan to keep pace with customer touchpoint variety

Having to perform hand-coded API integrations or costly custom integrations just to keep pace is a sure way to drain budgets. Ensure your integration platform connects with your current apps, whether you’re running Salesforce, NetSuite, SAP, Oracle, or any other app, as well as the ones you plan to use in the future, without requiring having to build connectivity.

  1. Customer data is your fastest growing asset – prepare to scale

There’s often no faster growing asset in the enterprise than customer data. And not just data, the sheer number of workflows around customer experience are set to skyrocket. Choose an integration platform that’ll keep pace. Because being forced to switch customer integration platforms later can quickly put the brakes on a customer experience initiative.

Set the foundation for customer experience success

To learn how to design your integration strategy to enable success with your customer initiatives, watch our webcast, “Data integration best practices in the age of the digital customer experience,” featuring Michele Goetz, Principal Analyst, Forrester Research Inc, and Ravi Dharnikota, Chief Enterprise Architect, SnapLogic. You’ll take away actionable insights for ensuring your organization’s data integration strategy is optimized for the digital customer. Register today!

Nada daVeiga is VP Worldwide Pre-Sales, Customer Success, and Professional Services at SnapLogic. Follow her on Twitter @nrdaveiga.

 

[1]Digitizing customer journeys and processes: Stories from the front lines,” McKinsey, May 2017.

[2]The Next Generation of Customer Analytics,” Ventana Research, February 2014.

 

 

 

New Podcast Series: SnapTalk

We are pleased to announce our new podcast series called SnapTalk. The series will feature short, 10-15 min. episodes on topics relevant to big data, data management and app and data integration. Our host for the series is Ravi Dharnikota, SnapLogic’s head of enterprise architecture. Each episode features a special guest in conversation with Ravi, such as SnapLogic’s chief scientist, Greg Benson.

This project grew out of the great conversations we have at Snappy Hour. Eating lunch as a group at least a couple of times a week and our weekly happy hour (called Snappy Hour) are big parts of the SnapLogic culture. And, invariably, the conversations at these gatherings range from the lightweight, such as the latest episode of Game of Thrones, to the complex, such as the future of Spark and what makes streaming data streaming. This podcast series is intended to capture the essence of those ad hoc discussions, get people thinking, and hopefully inspire additional discussions.

The first episodes are posted now and cover topics such as Spark, streaming data and Kafka. Stay tuned to this space for the next episode. The SnapTalk playlist is here and our new SoundCloud channel is here– I hope you’ll subscribe, and we welcome your feedback.

SnapLogic Best Practices: Deploying Projects Between Phases

[update – check out what’s new in our Spring 2016 release – the Metadata Snaps are also useful for Lifecycle Management requirements]

One of the areas our integrated data services team and partners spend time with customers early in a SnapLogic Elastic Integration Platform deployment is on deploying from one project phase to the other (Dev -> QA -> Prod). There are a number of different configuration options. In this post, I’ll describe one. First a few assumptions:

  • The enterprise Lifecycle Management feature is not implemented in this example
  • The phases that are in use are Development, QA and Production
  • Each phase in use is being managed at a project level as a separate project with in a single Organization Setup
  • The users have the necessary permissions to perform the operations described in this post
  • The enhanced account encryption feature is not in use in the current SnapLogic Org

Continue reading “SnapLogic Best Practices: Deploying Projects Between Phases”

Designing Ultra Pipelines: Types of Views

In my first post on SnapLogic Ultra Pipelines, I began to review aspects to consider when designing these low-latency pipelines. Once you’ve determined the right number of views, you need to determine the type of views. The unconnected views in an Ultra Pipeline act as the gatekeepers of the task, receiving and returning documents from the external applications. Continue reading “Designing Ultra Pipelines: Types of Views”

Designing Ultra Pipelines

Ultra Pipeline tasks are used to implement real-time web service integrations which require expected response times to be close to a few sub seconds. In the first series of posts I’ll outline some of the key aspects of designing Ultra Pipelines. In the second series of posts I’ll focus on monitoring these low-latency tasks.

Setting up Ultra Pipelines
Ultra Tasks let a pipeline, known as an Ultra Pipeline, continuously consume documents from external sources.

Because Ultra Pipelines tools are analogous to web service request/response architecture, the following aspects should be considered in designing Ultra Pipelines in SnapLogic. Continue reading “Designing Ultra Pipelines”

Attention Enterprise Architects: Sage Advice from Jason Bloomberg

bloomberg_rest_seminarIf you’re interested in enterprise IT architecture, chances are you’ve heard of Jason Bloomberg. The president of Intellyx, which is “the first and only industry analysis, advisory, and training firm focused on agile digital transformation,” Jason is a globally recognized expert on agile digital transformation who writes and speaks on how today’s disruptive enterprise technology trends support the digital professional’s business transformation goals. He is a prolific writer who is a regular contributor to Forbes, has a biweekly newsletter called the Cortex, and several contributed blogs. His latest book is The Agile Architecture Revolution (Wiley, 2013).

Recently Jason has published a series of articles that are directed towards today’s enterprise architect (EA), focusing on what’s new and what’s different in the era of social, mobile, analytics, cloud and the Internet of Things (SMACT). Here are the four posts he’s written so far: Continue reading “Attention Enterprise Architects: Sage Advice from Jason Bloomberg”

JSON is the New CSV and Streams are the New Batch

Mark MadsenThis is the 2nd post in the series from Mark Madsen’s whitepaper: Will the Data Lake Drown the Data Warehouse? In the first post,  Mark outlined the differences between the data lake and the traditional data warehouse, concluding: “The core capability of a data lake, and the source of much of its value, is the ability to process arbitrary data.”

In this post, Mark reviews the new environment and new requirements: Continue reading “JSON is the New CSV and Streams are the New Batch”