How to securely leverage data and achieve real-time personalization without a hyperscaler budget

How to securely leverage data and achieve real-time personalization without a hyperscaler budget

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Any digital company knows the potential value represented by customer data. They also know that like any raw material, there is a process that has to occur between collecting that data and being able to use it.

While being able to use data to enhance customer experience has always been a competitive advantage, the pandemic clearly drew a line between companies that could effectively leverage their data and those that couldn’t. A report by McKinsey & Co. showed that in the period from mid-2020 to late 2021, approximately 75% of consumers tried a new buying method, product or store and 80% of them liked the new way of doing things and intended to continue.

Simply put: If a business can’t provide the level of customer experience that connected consumers have come to expect, it will lose to the competition. However, achieving the personalization levels provided by corporations, such as e-commerce giant Inc., streaming platform Spotify Technology SA, and global retailer Walmart Inc., isn’t easy.

“Many companies do start and build [a marketing data platform] from scratch, and the problems early on seem very tractable,” said Chee Chew (pictured), chief product officer of mParticle Inc. “But then as new laws come out, as the platform changes … that puts you on this treadmill of always reinventing and reinvesting in the data collection.”

Chew spoke with theCUBE industry analyst John Furrier during a discussion prior to the upcoming AWS Startup Showcase “MarTech Emerging Cloud-Scale Customer Experiences” event, an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how customer data platforms enable companies to create value from customer data in real time. (* Disclosure below.)

Modern data challenges require new approaches to data management

A modern customer data platform has to not only provide real-time customer personalization, but also adhere to all relevant data governance policies, securely integrate with third-party data sources, and ensure that data is always high quality. It’s a tough bar to reach.

While previously working as vice president of consumer engagement at Amazon, Chew oversaw a team of several hundred engineers, all of whom were focused on collecting, cleaning and analyzing data. Employing such a large team is impossible for all but the largest corporations, placing real-time data analysis out of reach. Also, regardless of whether the team is large or small, “they spend 80 or 90% of their time cleaning data, getting access to data, like getting the right permissions. And they spend 10 to 20% of the time actually building models and doing the really interesting things that you want your data science to do,” according to Chew.

It is this gap that prevents companies from gaining real-time value from their data. Skipping processes means inaccurate insights, customers that head elsewhere, and data privacy transgressions that can result in security breaches and loss of brand reputation.

This is why companies such as mParticle are offering a way to simplify the customer data pipeline.

“Our core business is to take that grunt work and things that might be less exciting and bespoke to your business,” Chew said. “That’s the stuff that we get excited about.”

Real-time personalization steers consumer choices

Partnering with a customer data platform provider allows machine learning scientists and data engineers to off-load the tedious tasks of data management. They can then focus on building the models that will provide the real-time personalization experiences their customers want.

“The notion of when you go to one page or one screen on your mobile device and then you go to the very next page, that very next page has to be personalized with the things that you did just seconds ago on the previous one,” Chew stated. “It’s not enough to just collect the data, churn on it, do a bunch of like calculations, and then tomorrow figure out how to personalize it. It has to be in interaction time with our customers.”

An example of this would be an e-commerce outlet offering a newer version of a product a customer has placed in their check-out cart or a restaurant sending a discount voucher if a consumer searches for “places to eat lunch” in its area. According to Chew, mParticle’s ability to do this for any industry across all verticals results from the fact that there is a basic set of problems that affect all companies working to maximize the value from their digital transformation.

“If you look at the things that your engineers are doing … you’ll probably find that a minority of the work is really unique to your business and the majority are things that are common problems that other companies struggle with,” he stated. Take those problems away and companies are free to focus on the bespoke, unique and innovative aspects of their business.

The mParticle Customer Data Platform is based on real-time streaming architecture, enabling integration across multiple vendors to provide a holistic view of a customer’s data. And secure access through APIs and SDKs makes it easy for engineers to connect existing tools with the platform, reducing the time needed in third-party code management.

“We really work hard to empower our customers,” Chew stated. “We have a great reputation with our customers about really focusing on unblocking them and enabling whatever the heart desires.”

Here’s the complete video interview. For more insights into the latest innovations in marketing technology, be sure to register for SiliconANGLE’s and theCUBE’s coverage of the AWS Startup Showcase “MarTech Emerging Cloud-Scale Customer Experiences” event:

(* Disclosure: mParticle Inc. sponsored this segment of theCUBE. Neither mParticle nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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