Evaluating the right AI Platform for your business

As businesses are increasingly laying their focus on artificial intelligence solutions, it might be important to understand what goes into implementing these solutions.

Most business product and solutions have now taken to the tone of customer satisfaction, making every solution look the same. It’s only a matter of time, that they will all offer or at least speak about artificial intelligence. I would assume, it would become increasingly difficult for the businesses to understand the truth behind these systems. Continue reading →

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Agile Enterprises Need True Single Customer View

Businesses have implemented many point solutions to run their processes efficiently. However, these point solutions store data in silos, creating an unstructured environment which actually hinders effectiveness due to inaccuracy and speed

Inside this unstructured data environment, you will see point systems to manage their customer data, customer marketing and engagement (Marketing Automation platforms spanning email management, social campaigns, live chat, mobile engagement, loyalty tools and other), Commerce Systems (Point-of-Sale systems, E-commerce platforms), along with Intranet systems (Employee Collaboration, Document Management, Enterprise Content, Process Workflows), Supply Chain Management (For product lifecycle management), Enterprise Resource Planning and Financial Systems (Invoicing, Billing, Accounting)

Today you will see that some of these point systems have been consolidated to become platforms with feature aggregation. This solves data isolation to an extent but still does not draw a holistic view. Marketing Automation, Behavior Analytics and CRM are still offered as three different systems. With this, the challenge of unifying web behavior data with CRM or marketing automation data is not picture perfect. Marketing Automation platform has evolved to bring together Web/Email/Social marketing features but that would not be enough to understand the complete behavior of a single customer.

Without bringing data together, businesses cannot successfully implement effective data analytics, which is an integral part for process optimization to make accurate decisions. Department data stored in silos with no relationship with the other makes it extremely hard to drive business intelligence, and intelligence driven over siloed data can be very inaccurate.

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Today, due to inaccurate decision making, the business users get wrong insights.Some of these insights are translated to customer strategies, which puts customer engagement processes to risk. With customers constantly looking out for quick answers to their queries, intelligence cannot be latent and irrelevant. Real-time intelligence which can translate to customer strategies with less human intervention is the need of the hour.

Be it a personalized customer communication; or insights on how much discounts can be offered to a particular customer based on current NPV, accuracy in intelligence is a must to improve effectiveness.

Accuracy problem can be solved using the unified architecture which clearly builds data relationship between every data attribute gathered by all kinds of business applications. Coupling this with a data-aware system can solve the problem of data disorganization, latency, and redundancy. With the unified structure, you can organize your data between customer and non-customer fields and quickly extract customer data from the rest of the business data.dataaw

 

The deck below illustrates the gaps in the traditional solutions proposed to achieve single customer view and also elaborates on how a unified system can bridge these gaps and solve data problems for good.

 

 

SMAC Stack vs Unified Stack

Businesses are looking at implementing SMAC solutions in order to transform their digital business. If the objective was to get more insights into the business so that you can optimize customer centric processes and spends, then SMAC solves only a part of it. The Unified stack is much more agile and solves most customer centric problems, as the fundamentals of the unified architecture is to align and store data by individual customers

Unified Stack Architecture will help marketers align with 1:1 communication with every customer, which are the most targeted steps in conversion marketing. The stack also helps marketers understand and measure their marketing  spends accurately and enables real-time tracking of revenue and spends

But in the case of  SMAC Stack,  it picks data from different silos, and attempts to tag it based on available identifiers, and makes room for insight leaks and data redundancy, also due to its unstructured nature. But in the Unified Stack, data is tagged at the touch-points (client application) with necessary parameters.

The most important aspect of Unified Stack is that data tagging starts at the customer touch-point and extends across all other touch-points by maintaining a unified document for every customer, irrespective of the touch-point.

SMAC Stack vs Unified Stack

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