Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

mParticle Launches Calculated Attributes Enabling Product Managers and Marketers to Quickly Generate Insights from Customer Data without Tapping Technical Resources

mParticle, the largest independent Customer Data Platform, today announced the general availability of Calculated Attributes, enabling brands to turn raw streams of customer data into actionable customer insights. Calculated Attributes runs mathematical calculations on customer events and event attributes, enabling brands to unlock insights into customer behavior and preferences, like product category affinity or average order value. Within a few clicks, non-technical team members are empowered to design and leverage insights to hyper personalize customer experiences, without requiring code or technical involvement.

Product Managers and growth marketers typically require technical resources when developing data-driven personalization strategies, which is a time consuming practice for everyone involved. As brands struggle to remain nimble in rapidly evolving digital environments, driving speed and accuracy around customer insights become even more critical. mParticle’s Calculated Attributes takes a “no-code” approach to turning the raw stream of customer data into actionable insights, significantly reducing the time spent by engineers processing data and writing functions.

Recommended AI News: The Nobility Project Leads the Way When it Comes to BUSD Reflections!

PREDICTIONS-SERIES-2022

Calculated Attributes removes the bottleneck of relying on bandwidth constrained technical team members to design calculations while ensuring data accuracy. Marketers and product managers can use Calculated Attributes to gain granular details into user behavior such as lifetime value, total number of orders made, or the most frequent product categories viewed over a period of time. Users can then create hyper-specific segments for their engagement platforms, which ultimately power personalized customer experiences.

“Customer data is the fuel for optimizing customer engagement. The raw data requires activation to truly unlock its value,” said Chee Chew, CPO of mParticle. “Calculated Attributes makes it easy for brands to generate customer insights in real time and consistently across the business.”

Related Posts
1 of 26,533

Recommended AI News: Fourth Wave Energy Inc. Signs Merger Agreement to Acquire EdgeMode

Calculated Attributes provides three major benefits:

  • Granular Personalization: User attributes update in real-time after the calculation is made to power an up-to-date systematic understanding of customer behaviors for better personalization in Audiences, Profile API and in downstream systems.
  • Central Point of Truth: Attributes are defined and calculated in mParticle and then distributed. This helps remove confusion between teams such as a web and a mobile team that may be using slightly different definitions or calculations.
  • Simplified Calculations: Clients often feed mParticle with values they calculate in their BI platform. With Calculated Attributes replacing some of those values, a user no longer needs to maintain those calculated jobs.

To help brands get started with Calculated Attributes, mParticle is also releasing a use case guide that showcases Calculated Attribute examples and inspiration and how teams can create personalized experiences with them.

Recommended AI News: NavVis Adds Fresh Funding to Fulfill Its Mission to Digitize Commercial Buildings and Assets

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.