Rethinking employee benefits in a post-pandemic world

There’s no going back to the 2019 playbook, particularly for benefits. Learn what employees expect in the new normal, and how you can keep a competitive edge.

SugarCRM has boosted the artificial intelligence (AI) capabilities of its SugarPredict engine for marketing and sales intelligence, adding a sentiment analysis tool that determines prospects’ “emotional state and intent.”

SugarPredict is available on the Cupertino, California-based company’s Sugar Sell and Sugar Market platforms for automating and assisting with sales and marketing tasks. It’s also embedded in SugarCRM’s SugarLive multichannel customer communications application, the company said in a statement.

SugarLive is “designed to enable sales and service personnel to track the details of each customer interaction as it’s happening and effortlessly access customer information across all touch points and channels at the exact moment it’s needed,” SugarCRM said.

The omnichannel SugarLive customer service tool is available to SugarCRM customers with Sugar Serve licenses and provides real-time intelligence to customer service agents who are interacting with prospects online or on the phone.

Sentiment analysis works by using natural language processing (NLP) and AI to score the state of mind of a prospective or existing customer to determine best next steps, the company said. These could include escalating an interaction to a supervisor, presenting a “save-the-sale” offer, or moving to an upsell attempt.

Making the best first impression

SugarCRM chief technology officer Rich Green said sentiment analysis is intended to help SugarPredict users better handle crucial first interactions with prospective customers in the marketing process.

“You rarely get a second chance to make a great impression with a customer; it’s profoundly important to get each and every interaction right and connect on a deeply human level,” he said. “Sales and service professionals are under a great deal of pressure, as a customer’s business can be won or lost in a single misstep.”

Sentiment analysis is the latest in a series of AI-driven, marketing-centric improvements to SugarPredict. SugarCRM first released the software in January as a sales tool for SugarCRM’s Sugar Sell users. SugarPredict for sales is billed as an automated cloud software solution that can intelligently enrich the customer data entered into CRM systems to ensure quality and consistency.

In May, SugarCRM made SugarPredict available to users of its Sugar Market marketing intelligence platform to help marketing teams with automated predictive lead scoring.

Sugar Market is a customer lead-cultivating platform that helps marketing teams with tasks like quantifying how website visitors interact with digital marketing materials; assisting in the creation of emails, landing pages, and forms; qualifying leads with lead-scoring models; and aligning with sales via automated hand-offs of qualified leads.

Rethinking employee benefits in a post-pandemic world

There’s no going back to the 2019 playbook, particularly for benefits. Learn what employees expect in the new normal, and how you can keep a competitive edge.

Presented by Tealium

Businesses have long relied on data collected through third-party cookies to fuel their targeted top-of-funnel marketing campaigns. In the era of big data, third-party cookies offered a compelling, data-driven way for marketers to target and measure otherwise anonymous users. But privacy concerns brought about significant browser changes that eliminate support for third-party cookies.

Digital data signals are becoming more restricted, and third-party cookie loss is just one symptom of a larger trend that includes increased regulations, identifier restrictions, and walled-garden ecosystems. The cumulative impact of these trends could lead to “data deprecation,” which is a daunting way of saying that as marketers, we need to rethink our data strategy.

To continue providing the best customer experience (CX) possible, brands will have to change any strategy in place today that relies on third-party cookie technology and identifiers. A good first step is to move to a first-party data strategy.

Companies have historically collected first-party data, but without a purposeful data strategy focused on actually using the data obtained directly from customer relationships, it can sit in silos and fail to achieve specific business outcomes. Brands should activate this data and create a more intentional, focused, and effective plan to maximize the asset.

For most companies, a first-party data strategy will require them to refocus on the customer journey itself — the direct relationship you have with your customers (not through a marketplace or intermediary) — and shift away from customer acquisition strategies. In the new world without third-party cookies, our ability to recognize, understand, and engage digital customers in pre-purchase situations may be hindered.

Thriving in the new world involves fueling CX across the full customer journey — including post-purchase. A traditional online marketing strategy, for example, may focus on acquiring that first-time buyer — relying on third-party data or cookies to identify who the buyer is, what their preferences are, and which tactics may entice them to opt-in or make that first purchase. Without third-party data and cookies, these strategies disappear.

By using first-party data, however, brands can glean insights from past purchase behavior, brand loyalty, or even future intent (customer wishlists) and offer an experience that focuses more on retention and loyalty.

In our latest ebook, we helps brands get ahead of the strategy game in four simple steps:

STEP 1: Place value on data collection, identification and consent

Use the data you obtain directly from customer relationships — instead of buying it from a third-party or collecting it through a third-party cookie. The data will be more accurate and current, which is better for creating the right type of experiences for buyers. Identification is core to the value exchange/consent strategy.

STEP 2: Re-strategize your targeting mix

There are generally three buckets of targeting that any brand aims for; contextual, audience, and 1:1 (as in retargeting or personalization). A first-party data strategy can play a role in revisiting contextual targeting.

STEP 3: Make your first-party data a differentiator

Every brand will still need to be effective at contextual targeting, but where you can differentiate and distance from competitors is how you can leverage your first-party data to optimize performance.

STEP 4: Facilitate a value exchange across the full customer journey, not just at the start

Thriving in the new world involves more than just acquiring new customers. Take care of the ones you already have! First-party data can help fuel the value exchange across the full customer journey — including post purchase.

Once the shift away from third-party cookies accelerates in 2022 and into 2023, those who are ready will stand out from the crowd with relevant, timely, and insightful customer experiences compared to the generic, one-size-fits-all experiences of the competition. Those who haven’t prepared will need to build that strategy out from nothing — all in an environment where there’s simply less data available. Build a first-party data strategy today that can stand the test of time and sustain your advertising, marketing, and CX campaigns.

In our latest eBook, “In a World Without Third-Party Cookies, a First-Party Data Strategy Takes the Cake,” we offer 4 key steps that help guide you towards a new first-party data strategy and keep you ahead of the game.

A Customer Data Platform (CDP) can help you build that comprehensive view of your customer in order to deliver a relevant and timely customer experience. Ready to start taking action but still not sure exactly where to start? Tealium’s got you covered. Get a personalized demo to see first-hand how Tealium can help you start delivering a first-party driven approach!

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