As the kids return to classrooms this fall, I’m reminded that school is never really out for our industry.
We’re seeing a blistering pace of change in mar-tech innovation. Marketing teams face intense pressure to engage customers across growing numbers of channels and devices.
Much of it requires new marketing skill-sets and continuous learning, with a focus not just on the fundamentals, but on advanced use cases in today’s marketing technology.
What do I mean by advanced use cases? Think of them as a curriculum of advanced capabilities, enabling marketers to engage customers using the most sophisticated methods available. Some good examples of this are:
- Advanced Analytics
- Voice of Customer (VOC) Optimization
- Mobile App Optimization
These advanced mar-tech capabilities allow the enterprise to scale efficiently and effectively. They support organizational complexity, often across geographical and departmental divides.
And all of these use cases rely one core element: the ability to collect, analyze and act on omnichannel data across the entire customer experience. That’s what makes the new marketing reality so challenging. It’s also why the opportunities are so exciting.
We talk a lot about engaging customers across the omnichannel journey, but in fact, it’s difficult and rarely fully executed. Data is fragmented, some of it isolated behind proprietary vendor firewalls. Delivering the right information, at the right time, to the right consumer requires a sophisticated and highly orchestrated technology stack.
Forrester analysts show how far we have to go, with one recent study revealing that less than 40 percent of companies surveyed could link email data to customer activity in other channels, and “the situation deteriorates with point-of-sale systems, display advertising, etc.” Only 13 percent of companies applied extensive personalization across multiple channels.
So let’s go back-to-school to consider four advanced use cases of the several areas powered by mar-tech innovation:
1. Apply Advanced Analytics
Marketing teams need to move from simple, surface-level dashboards to interactive analysis, using dynamic statistical models. Advanced analytics delivers capabilities like attribution and correlation discovery to explore hidden relationships among seemingly disparate channels, and generate more information about why, when, and where consumers interact with brands across all marketing channels and platforms.
The “what if” analysis enables marketers to explore likely outcomes, depending on which actions marketing teams take. Granular, multichannel data from both online and offline channels is core to powering smart, data-driven decision making processes.
2. Optimize Mobile in Real-Time
Last month, I referenced the Google research conducted by Forrester which showed that 82 percent of consumers use their mobile devices for in-store purchase making decisions. This puts mobile apps front and center.
Marketers increasingly rely on app analytics to understand how an app is being used. They also continuously test and optimize different content and experiences to boost engagement. The key to executing effectively on this use case is the ability to act in real-time as you identify customer actions and preference, as opposed to the more common and time consuming task of submitting changes to the App Store.
3. Reduce Call Center Time to Value
High-value customers need to be quickly routed to the best call center agents to improve the overall experience. Effective execution requires the agents to have immediate access to customer profiles so that they may prioritize which customers receive premium service and which are deprioritized.
Naturally, the more data-rich the profile is with information from the omnichannel customer journey, the better the routing and service level will be. Additionally, access to relevant data in the customer profiles will improve the agent’s ability to address issues more effectively, increasing customer satisfaction.
4. Optimize the Voice of the Customer (VOC)
VOC describes the in-depth process of capturing a customer’s expectations, preferences, and aversions. Capturing VOC feedback in real-time and making it accessible as part of a user’s profile also adds additional value for downstream engagement and cross-channel targeting.
The key to optimization is targeting only select segments of customers for survey questions to ensure business and development teams are aligned with strategic customers.
To achieve this, you need to first refine survey delivery by segmenting customers based on key metrics such as profile attributes or engagement models. This way, you can extend more survey invitations to high-value consumers, or target users that fall into specific categories.
The ability to collect, analyze, and act on omnichannel data across the entire customer experience is the key to success for each of these use cases. Armed with this, you can build customer profiles, prioritize business actions, analyze macro trends, optimize customer engagement, and drive one-to-one personalization.
Gaining a wider understanding of the customer journey isn’t easy, but certainly possible if you are thoughtful about mar-tech strategy. This is definitely something to ponder about this back-to-school season.
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