There are clear benefits for companies allowing website users to login with social media platforms such as Facebook, Twitter, Amazon, and Google. But the ease of user access that social logins make possible comes at a price: The platforms learn a great deal more about users’ buying and searching behavior via these agreements — information that could wind up helping the company’s competitors (including the platform itself) down the line.

Leading marketers in the travel sector are using machine learning not only to measurably improve business outcomes but to fundamentally redefine what those outcomes should be. Travel marketers who take advantage of the large volumes of data their organizations collect will continue to pull ahead of their rivals.

Companies often treat social media as the conversation that represents what consumers are saying about any given brand. But research shows that online and off-line conversations are different beasts. Even though they both drive sales, they need to be measured and managed separately.

Our research on KPIs suggests there is no clear best practice when it comes to relying on data versus intuition to make strategic decisions.

Oftentimes contending with overwhelming quantities of data, the health care industry could lessen its reliance on intuitive decision-making by making better use of machine learning.

Three principles show how successful retailers are responding to digital disruption and using insights to improve customer experience — not just in the end-of-year rush, but year-round.

Recommendation engines influence the choices we make every day — what book to read next, which song to download, which person to date. But digital recommendations are also a source of unintended consequences. Research shows that recommendations do more than just reflect consumer preferences — they actually shape them. Given that perfect prediction is not possible, retailers and managers must be aware of the potential discord from unintended side effects of their recommendations.

To thrive, retailers must match their belief and investment in machine learning with incentives that clearly connect to their broader strategic goals.

Many B2B companies seek to grow beyond traditional product lines by venturing into new services. Yet they often overlook the opportunity to capture sales from free services they provide. This article outlines the free-to-fee, or F2F, service transition. It shows how to inventory free services (categorizing them as profit drains, distributor delights, competitive weapons, or gold nuggets) and lays out a path for profitably generating revenues.

According to Northwestern Mutual’s chief marketing officer, marketing should be more than a support function — it should be a strategic growth driver. In this video, Aditi Javeri Gokhale describes how the company used KPIs to train machine learning algorithms to build an online experience that pairs customers with financial advisors. Its success rate: over 95%.

Digital customer service is becoming more widely adopted, but one place it falls short is in the language and phrases it uses. Many digital service platforms use words that alienate customers rather than engage them; selecting customer-centric language for chatbots and service platforms can make a significant difference in customer satisfaction.

The popular perception of Twitter as a social media “echo chamber,” where people only receive and retweet opinions that match their own, does not reflect the data about users’ actual engagement. The average Twitter user propagates more mainstream content and follows a diverse group of users — and this has implications for social media marketing.

By featuring Colin Kaepernick in its latest “Just Do It” campaign, Nike has made a deliberate decision to increase the appeal of its brand among younger, liberal, and ethnically diverse consumers while risking not only a portion of its existing customer base, but also its overall reputation.

Insight into what customers really care about often is hampered by the quality of the information being collected. Big data can support smart market research, but only if researchers embrace psychometric best practices and the basics of understanding what it is they want to measure and how. That means asking the right questions, asking enough questions, understanding how to weigh questions, and taking into consideration how people felt about the brand to begin with.

What can digital technologies do to help an organization solve customer problems? And what solutions will customers find valuable? It’s only when leaders wrestle with these questions that a digital strategy can emerge. To get there, organizations need to create a portfolio of business experiments and engage with customers to gain insight into their problems and potential solutions. The intersection between what’s possible and what’s desired is where a business will succeed.

Executives in the automotive sector believe that machine learning can help them achieve their marketing goals, but that doesn’t necessarily mean they invest in that ambition.

E-commerce and omnichannel retail strategies have revolutionized the way consumers buy products, but maintaining consistent pricing across global markets can be an obstacle for organizations. By harnessing a focused data science strategy, organizations can avoid pricing pitfalls.

Join us on Twitter to discuss how next-generation measurement can drive change in your organization.

Our 2018 Strategic Measurement research shows that companies using machine learning to optimize business processes and decision-making have distinct advantages over those that aren’t investing in ML. By using ML technology to make KPIs more predictive and prescriptive, these data-driven companies are redefining how to create and measure value.

How should companies launch products in times of uncertainty? Should they “wait and see” until uncertainty resolves — or commit to a full-scale launch and ride it out? Conventional wisdom says being early to market is the right choice, but that is not always the case. Many companies can benefit from a mixed, “act and see” approach.