Big Data, Analytics and Metrics to Make Better Decisions
To properly align the needs of your business with a strong CRM system, a best practice is to strategically leverage what is known as the ‘SMART’ approach, a methodology that big data expert, Bernard Marr, explains in his recent book, Big Data: Using SMART Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance. The SMART approach enables you to focus on high-level objectives that dictate what you want to achieve through your CRM initiative; at the same time, the SMART approach also takes 360-degree data points into account, which complements and supports the overall strategy.
Start with Strategy
• Start with the end point in mind, and identify what your desired CRM-based business objectives will be. You also need to proactively consider how to navigate above and beyond any potential roadblocks that may prevent successful outcomes.
• Challenge yourself and other stakeholders to further identify any secondary or unanswered questions that may arise on the path towards satisfying your CRM objectives.
• Think globally to also determine your organizational pains – especially any pain points that may hinder or mitigate your long-term CRM success.
• Establish what it is you want to understand about your people, your delivery of goods and services, your competition, and most importantly, your customers.
Measure Metrics and Data
• Address how you are going to act upon any information that emerges during the first step in the SMART approach – especially information that leaves you dissatisfied in some way.
• Define the appropriate CRM data collection methodology, and then describe the data volumes and data veracity.
• Determine how you will turn intelligent CRM data into insightful ideas which can be harnessed across your business and daily operations.
• Identify the ways in which you will translate CRM- gathered data into very simple and digestible visualizations – such as graphs and info graphics – that can be distributed and understood by mission-critical, cross-functional teams.
• A robust CRM initiative will produce ongoing metadata which you will need to effectively mine and analyze on a regular basis.
• Transformational data should be gained from your CRM initiative, and your business needs to be armed with up-to-date, detailed insights on customers.
• Change is necessary – you need to identify and implement business process and performance improvements which will drive revenue and profitability.
Big Data Transforming CRM
Big data has one basic organizational goal: to better understand and target customers to achieve enterprise-wide success. Building upon this notion, big data can allow CRM to move from a position of understanding or where the customer has been to actually predicting where the customer will be. Not only can big data provide predictive analysis, but in some cases, it can offer these predictions in real-time. These are the two most significant developments, as they completely change the game of CRM from one that captures a snapshot of the past, to one that creates offers for the future, and changes them immediately should the customer’s behavior or criteria change.
“Big data can allow CRM to move from a position of understanding or where the customer has been to actually predicting where the customer will be”
What will be needed in big data-infused CRM is the ability to add predictive behavior (building algorithms to capture the data and analytic tools to assess the findings, as well as coding to make the data ‘alive’ to respond to the behavior changes). Ultimately, big data CRM is the newest and most powerful data tool available to transform organizations.
Social, Mobile, Apps and Cloud
There’s another relevant acronym that can be applied here known as SMAC or more specifically, Social, Mobile, Apps and Cloud. The best place to start is to realize that they are all connected. These are not individual tools that should be used separately; they are components that interlock and connect to make a very powerful CRM machine.
The following are three steps to start building the SMAC-empowered CRM machine:
• Analyze all Social, Mobile, Apps and Cloud-powered assets and determine what data they will provide you, and if you can reasonably access and analyze CRM data.
• Determine where these assets will reside, and who will assume ownership over them. For example, if you are part of a major company, it is necessary to consider if SMAC assets will be a sole asset to one line of business, or if they can be deployed as joint resources between multiple business units. If you have sole ownership over SMAC assets, you should certainly consider what other business units would benefit from the knowledge generated from this asset.
Identify How SMAC Assets
Combined Help Achieve Current
• Your business objective is very likely to increase sales by some percentage in a specific target segment. To do this, you should answer the following questions:
• Social – Is this channel providing customers with satisfaction or dissatisfaction? Does it help to determine or uncover customer needs?
• Mobile – If sales can be made on a device, how effective is my mobile channel and is it fully-optimized?
• Apps – If you do have Apps, what data can you track from the customer interaction?
• Cloud – What information is stored about customer purchase behavior that you can access and turn into trend analysis?
This example exemplifies the power of the connected data. With all these points connected, an organization can create desired products, identify the most likely purchase behavior, drive customers to a desired purchase channel, and assess purchase and measure re-purchase potential. SMAC can also assist with product and offer development, as well as customer decision journeying and loyalty.
Author: Anne Legg, VP - Strategic Marketing, Fiserv Source: CIO Review
Kalyan Banga203 Posts
I am Kalyan Banga, a Post Graduate in Business Analytics from Indian Institute of Management (IIM) Calcutta, a premier management institute, ranked best B-School in Asia in FT Masters management global rankings. I have spent 6 years in field of Analytics.