Martech Starter Kit
Monetate

What was Montetate’s motivation for its Intelligent Personalization Engine?

There’s a clear attitude shift among many consumers, asserts Lucinda Duncalfe, CEO of Monetate. “What used to be creepy is now expected: ‘I want you to know me across channels’; ‘I want you to know my style preferences.’ That’s becomes a bar retailers need to meet.”

AI and data integrations in the Monetate Intelligent Personalization Engine are designed to deliver an experience that makes customer feel like they’re known to the brand, Duncalfe says. “They’re more likely to feel good about the brand, and more likely to buy,” she says. “There’s a clear consumer preference for relevance that leads directly to revenue for retailers.”

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What marketing problem does it help tackle or opportunity does it help marketers grasp?

Personalization by segment costs the same each time you slice your customer data, but the segment is only half. If you keep slicing, it costs the same,

MarTech SK – Monetate 2017.pdf

Download a PDF version of this article.

but each segment becomes a smaller and smaller slice, Duncalfe explains. The payback ends at about 12 segments, she

adds. After that, there aren’t enough customers in each segment; the personalization becomes cost-prohibitive based on

the potential return.

Instead of creating unique experiences for each individual customer, build the right experience from the offerings you already have available for your customers. It’s kind of like the difference between Baskin Robbins’ 31 flavors and more than a dozen toppings, and Cold Stone Creamery’s eight primary flavors and about 30 “mix-ins,” which translates to an extensive array of “personalized” combinations without all the costs (and potential loss) of stocking 31 flavors.

In other words, once marketers have set a goal for a campaign—for example, increase average order value—they can use Monetate Intelligent Personalization Engine’s machine learning capabilities to optimize the experience in real time using the existing offers and items that customers are most likely to respond to and that will meet the marketers’ goal.

What does it take to add this product to a marketing organization’s existing tech stack?

• Estimated implementation timeframe – Three weeks is typical.

• Integrations – Monetate offers two API-based integration solutions. One is a Javascript API, embedding Monetate’s solution on a customer-facing page. The other is a server-side API that cuts out the need for Javascript, and is more suitable for non-Web integrations, such as mobile apps, in-store kiosks, and point of sale.

• Dedicated administrator? – No full-time administrator needed. Usually, marketing team member scan take Monetate admin duties into their larger set of responsibilities.

• Typically, who are the users – Digital marketing professionals are the more common day-to-day users. Most often the solution is owned by a digital marketing manager or director. Other stakeholders who may need infrequent access to Monetate include data analysts and the IT team.

• Amount of initial training for users – Approximately 10 hours, including preparation and homework time. The core training unit is a half-day online conference, augmented by live and recorded webinars and a knowledge base. Face-to-face training is available.

• Data sources – Most commonly are CRM, purchase data, and customers’ web traffic history. Marketers can integrate data from any matchable source.

• Notable process changes – No specific changes for organizations already working with personalization. May help organizations reorient personalization and optimization teams.

Can you test the product before purchase?

Monetate offers customized, objective-driven demos, but not an unsupervised test or trial version.

Does it come with any consulting or implementation services?

Consulting and implementation are available at additional cost.

Who “owns” it over time and where does it sit?

Monetate’s model puts the marketing department in charge of the solution. Deep integration with other data sources may require coordination and collaboration with other arms of the business, such as IT.

What’s the enterprise pricing model?

Instead of a typical site license or per-user model, Monetate’s license is based on the number of marketing channels in the deployment, and the total number of unique visitors to the company’s site.

What’s the projected time to ROI?

Monetate does not publish a public ROI calculator. The company claims that its most successful clients have achieved payback within two weeks.

What’s the solution’s competitive advantage?

Monetate positions itself as an influence engine, not just a recommendations platform. It aims to deliver superior results by tailoring not just product pushes, but an entire customer experience based on an expansive net of data, processed in as near to real time as possible. These customized, personalized experiences are delivered through multiple touchpoints, with a feedback loop that trains the Monetate engine and informs the marketer.

What’s the word from a beta customer?

“The Monetate Intelligent Personalization Engine has quickly proven itself beneficial to our business. In less than three weeks, two of our brands saw a 5.6% and 2.2% lift, respectively, in revenue per session. Without the Engine, that lift would not have been possible and we would have missed out on hundreds of thousands of dollars in revenue.”

          –Adam Godfrey, senior digital marketing and analytics specialist
at luxury retailer Frontgate

What’s an analyst’s take?

“Leaders must help organizations prepare for the next evolution of personalization, which will rely more on the pillars of individualization rather than on segmentation.”

          –Brendan Witcher, Principal Analyst at Forrester Research

Where can I find more information?

> Check out the Monetate Intelligent Personalization Engine splash page

> Read reviews about Monetate on G2Crowd

About the Author

Ginger Conlon found freelance writer Jason Compton shoved in a desk drawer by her predecessor at CRM magazine. He has covered CRM and marketing topics extensively since 1999, largely in her service.​

Find him at @jpcwrites and on LinkedIn.