Apr 1, 2021 5:00 AM PT
Over the course of the past year, adjusting to the challenges of the pandemic on business has made the customer relationship management system an essential tool for maintaining and growing a customer base. As a result, CRM platforms have evolved into something more than just a digital Rolodex to manage customer contacts.
A key aspect of succeeding in customer management tasks involves addressing the customer experience. Brands and retailers need to become customer-obsessed in 2021 in order to improve the customer experience, suggested Jennifer Conklin, sector lead of unified commerce at Capgemini North America.
With most workers continuing to work remotely, CRM has become an important tool for managing relationship risk. Financial firms have to deal with market and operational risk, consumer retailers have to focus on supply chain risk, and all companies have to keep an eye on economic risk.
Feb 24, 2021 5:08 AM PT
As consumers get comfortable with their newfound digital wallets and gift cards, marketers must continue to adapt their strategies to changes in shopping behavior to better finesse the customer experience.
Both consumers and vendors have had non-stop adjustments. Lockdowns and social distancing requirements accelerated the adoption of new technologies. Commerce trends that were on the horizon pre-COVID-19 were suddenly adopted at a brisk pace. Online food ordering, curbside pickup, and BOPIS (buy online, pick up in store) are presenting new challenges to store owners and brand marketers.
Commerce analysts do not see consumers shedding their newfound buying options in the wake of a post-pandemic marketplace. Concerns for health safety, social distancing, and remote working will remain as the center stage in the daily lives of millions of shoppers.
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The digital transformation times, they are a-changing – and so, too, must digital transformation metrics. “The primary measure of success last year was survival,” says David Cushman, research director in the emerging technology practice at IT consultancy and research firm HfS Research. “Transformation was thrust on so many.” Companies and their IT organizations had no choice but to do what needed to be done – quickly. Speed, Cushman says, was the primary KPI.
Having completed any number of initiatives (many that had been on the digital to-do list for some time), organizations are looking at what’s next.
“Companies relied heavily on automation and advanced capabilities like Artificial Intelligence (AI) and edge computing to pivot their operations and thrive through the pandemic,” says Goutham Belliappa, vice president of AI engineering with Capgemini North America. “In 2021, they will see the true value of these investments as they find
1. Be honest about your goals and needs
Sharing business objectives and goals is essential to establishing a successful MSP alliance.
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“The MSP must be able to match that understanding with acknowledgement of how their approach fits those objectives,” Lamendola explains. “An organization that approaches an MSP relationship with an upfront investment in developing a shared vision on how the organizations will work, interact, and evolve together will typically result in a positive experience.”
A policy of honesty and openness is always highly effective, since it reflects the same basic principles that organizational effectiveness methodologies are built on: communication, collaboration, shared goals, measurement, analysis, and continuous improvement. “When the MSP relationship is rooted in an extension of the organization’s structure and culture, the experience is mutually beneficial,” Lamendola states.
Enterprises building data lakes and warehouses have been turning to third-party vendors to bring in data. Building connectors to applications likes Salesforce is tedious and requires data engineering expertise. Plus, the SaaS platforms change up their data schemas and API details.
These data pipeline vendors extract data from the source systems and load the data into the warehouse. They will also clean up or sync the data between different systems, either before it gets to the warehouse, or after.
Today, more and more companies are opting for the latter.
With the first approach, transforming the data before you get to the warehouse, you lose traceability, said Goutham Belliappa, vice president of artificial intelligence engineering at Capgemini North America.