Introduction

Have you observed Brands following you?

Have you seen your mailbox with emails from the brands?

Do brands follow you on your social apps?

Do you observe competing brands targeting you with similar products?

You’ll often see brands target you via various channels for products and services you were never or no longer interested in. At times it is quite frustrating. Let’s understand the rational and mechanics behind this. How are brands doing this and how they can avoid “hyper-personalization”.

Over the years, consumer interaction with brands has undergone a myriad of changes. Consumers aren’t interacting sequentially anymore. They have access to multiple devices and channels. While interacting with the brands they expect the brands to remember them – where and how they left in the “consumer journey”. Let’s assume that you have raised a product delivery issue in the mobile app. You have reached out to the customer care to follow up, but you must explain the issue right from providing the order no. Wouldn’t you feel frustrated? There are high chances that you will discount that brand for your next purchase or go social about the tedious experience.

According to McKinsey, 71% of consumers expect companies to deliver personalized interactions and 76% get frustrated when companies don’t. The study also mentions that organizations that offer personalization are driving 40% more revenue. While this may seem an effective strategy to boost sales, it makes consumers wary of the invasion of their privacy. Being tracked for personal traits and online behavior could be awkward. Hyper personalization can make them uncomfortable unless they are made to feel special. Studies suggest that consumers have mixed feelings about personalized online ads. Only 17% believe personalized ads are ethical. That leaves marketers wondering, how to strike a balance between privacy and personalization?

Marketers need to have a better insights into Customer lifetime value (CLV). Brands must leverage contextualized hyper personalization at scale. They must focus on coordinated Marketing across all touchpoints, rather than calendared and personalized events. Here, effective communication is the key – deliver the right message at the right time to the right customer on the right channel. Let’s understand how brands can leverage Decisioning and Orchestration platforms for effective communication.

What is Decisioning and Orchestration management?

Decisioning comprises of people, process and technology which enables a brand to decide the next best action (NBA) – who, how, what, and where to connect with the consumer. It is powered by data and works along with Orchestration, to provide intel to the application layer. Decisioning and orchestration together facilitate relevant activations and real-time omni-channel marketing. Marketers must leverage these to deliver cross-channel, real-time solutions. Without this function, channels would remain siloed and customer experience would be disjointed.

Decisioning & Orchestration in MarTech

A marketing ecosystem broadly consists of the three essential components – data, intelligence, and activation – to deliver a seamless customer experience across channels. In the above MarTech reference architecture, Experience Data and Experience Activity Hub belong to the data layer. The Analytics Hub is where all the intelligence is built, and Experience Management & Experience Delivery are a part of the activation layer.

The data layer integrates with various sources and channels to consume data and creates multiple segments. They include customer profile, behavioral, geographical, transaction, sales, campaign data, customer service, and RFM (recency, frequency, monetary) segments. An RFM analysis enables brand marketers to target specific customers with relevant campaigns resulting in better ROI, better customer retention and a high customer lifetime value. Data is processed and standardized to create customer 360 profile. The unified customer profile is fetched by the MarTech platforms for further analysis.

In the intelligence layer, the decisioning engine operates to analyze a customer’s past behavior and comes up with the expected future behavior to determine NBA. Decisions may be taken locally or centrally. Local decisioning is done at the channel level, in the activation layer, based on the customer behavior at a specific touchpoint. Central decision-making is for a group of customers based on the larger data set. Implementation of central decisioning is done in the activation layer.

Orchestration is about optimizing how decisions are coordinated and executed across multiple channels and marketing platforms. It goes beyond traditional personalization techniques and leverages data from customer touchpoints across multiple channels and sources.

For e.g., a user adds a product to the cart from the mobile application. An error occurs while making the payment and the product is no longer available in the cart. The user now turns to the web application but can’t find it there either. He navigates to the contact us section and reaches out to customer support. The customer feels a bit lost in the IVR (interactive voice response); meanwhile the chat robot pops up with a “May I help you?” message. The chat platform recognizes that user is stuck with an order which is not yet processed, courtesy, the orchestration solution. It also understands that it is a high-value customer, and as an NBA it triggers a call from an agent to the user for quick assistance. The agent is already aware of the case history and successfully creates an order on the user’s behalf. The order is now available in the customer’s order history section, and he receives a successful order creation email.

To compensate for the unfruitful experience, the decision engine decides to send a bonus coupon offering a 20% off on the next purchase. The orchestration platform triggers a 20% off campaign wherein the user receives an email and an SMS push. The user clicks on the 20% off coupon and gets redirected to the product catalogue, where the CMS displays customized products. During the next purchase, the ecommerce platform auto-applies the 20% off coupon, leaving the user with a smile on his face.

In this entire process orchestration and decisioning are working in tandem to focus on customer touchpoints and create the best cross-channel experience.

Decisioning and Orchestration in business strategy

Customer experience is always at the center of marketing orchestration. Marketers are now utilizing the power of integrating marketing use cases with operational/service use cases. Here’s an example – Imagine a customer buying a new espresso machine. For some reason the machine is not functioning as expected. The customer creates a ticket with the service team. The marketing team engages with the customer by sending him tips and tricks for brewing a good espresso, which is a valid use case from the marketing standpoint post a new product-buy. However, the customer does not welcome such information, adding to his frustration, leading to an unfruitful customer experience.

If the marketing team is aware of an opened service ticket by the customer, they would refrain from sending the follow-up marketing information, and provide something else related to the opened ticket. This is only possible with the orchestration and decisioning solution, which uses multiple channels and data from varied sources to come up with the next set of actions. This makes the overall customer experience a bit more organized and fruitful.

Data Key to Marketing orchestration and decisioning

There is a lot of data being produced by the consumers. As per Statista, consumers will produce and consume 181 zettabytes of data by 2025. The success of any marketing initiative depends on how well the data is collected, stored, and leveraged in the tech stack to be consumed by the intelligence and activation layer. It starts with collection and storage. It is important that brands collect and store 1^st, 2^nd, and 3^rd party data from varied resources. Data enrichment enables a holistic view of a customer wherein the data is processed via multiple massaging rules. Data scoring takes a 360-degree approach while considering all the customer touch points. Following are the key parameters while doing the data scoring –

• Recency – Has the customer interacted with the brand recently?
• Frequency – How often does the customer make a purchase?
• Intent – How has the customer shown the intent to buy?
• Type – Does the customer fit into the ideal customer profile?
• Engagement – How deeply has the customer interacted?
• Monetary – How much does the customer spend on purchases?

Data Intelligence enables brands to use data in the right activities with the right offers at the right time. A decision engine determines the NBA and an orchestration engine activates it via the right medium in the activation layer.

A good data architecture empowers brands with a near perfect NBA, well-orchestrated marketing campaigns and acts as a robust base for measuring marketing dollars.

Conclusion

Orchestration and decisioning play a pivotal role in providing an organized and collected customer experience. Orchestration is how brands operationalize decisioning and make channels do things by providing the right decisions.

There’s data orchestration to ensure the right data gets to the right place at the right time and then there’s customer orchestration to ensure the right material reaches the right customer at the right time.

Brands need to take a bold step in investing into decisioning and orchestration solutions. It requires substantial time and effort to build such solutions. But once built, it can change the way marketing is done, creating a win-win world.

LTIMindtree offerings

LTIMindtree has enabled one of the world’s largest cosmetics company – spanning across categories of hair color, skin care, sun protection, make-up, perfumes, and hair care – to implement a decisioning and orchestration solution which integrates with client’s existing MarTech stack. The client was looking for an integrated 360-degree customer view across all the touch points to drive personalized interaction via customized and consistent customer experience across all the existing channels and devices. This solution enabled brand marketers to target existing and potential customers with personalized products and campaigns based on demography, buying patterns and loyalty information. More than 52 brands were onboarded to this solution and are currently benefiting from the data driven marketing intelligence. Brands have already realized a 20% increase in the customer volume across brands post the solution launch.

Please click here to understand more about LTIMindtree’s offering in this space.

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