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Drive revenue through tailor-made experiences with advanced technology

Jess Vadino, global digital strategy and experience leader at SoftServe, believes retailers are not reaping the benefits of a targeted personalization strategy. Retailers must evolve to become agile, responsive, and proactive.

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November 27, 2019

By Jess Vadino, global digital strategy and experience leader, SoftServe

The retail industry has long embraced the potential value of personalization, with the publication of various studies such as higher purchase intent, greater order value, improved marketing effectiveness and more. Many retailers have implemented conventional targeted messaging tactics using demographics, explicit preferences, and previous transactions. Yet 80 percent of customers remain unsatisfied with the level of personalization in store and online, according to a 2019 NetSuite study. To deliver the individualized experiences customers demand — and realize significant returns at scale—retailers must invest in advanced technology.

Enterprise retail companies, like massive container ships, move cautiously and slowly, occasionally correcting course after considering latent or incoming information. Most retailers don't maximize efforts and reap the benefits of a targeted personalization strategy. To create hyper-personalized experiences with realtime data and deliver bespoke content and offers to consumers, retailers must evolve to become agile, responsive, and proactive. The transformation from ponderous to nimble begins with data.

However, with data housed in disparate systems, companies struggle to acquire the level of customer intelligence needed for hyper-personalization. Delivering individualized experiences requires retail to adopt a design-thinking methodology, construct a 360-degree view of the customer, and enable tools that deliver hyper-personalized experiences.

Putting the person In personalization

Сreating a personalization strategy is directly dependent on a deep understanding of the customer which can only come from adopting a design-thinking mindset — a human-centric, solution-focused approach. Adopting an empathetic customer perspective allows retailers to better identify challenges or pain points, and respond with qualitative and comprehensive solutions.

A strong personalization strategy uses design-thinking methodology to provide actionable and emotional solutions that directly address customer wants and needs at every stage of the buyer's journey.

To be fully effective, design thinking requires an inherent cultural shift — promoting collaboration and transparency throughout the company. Cross-functional teams are brought together to share information and ideate on customer personas, characteristics, emotional states, and more. From this shared understanding of the customer, these teams create solutions. The benefits of design thinking have the potential to expand beyond the application to personalization and pervade through departments such as design, customer service and even support functions such as HR.

Design thinking methodology cultivates a deep understanding of customer needs and desires, and is fueled by data. To develop a 360-degree view of customers, retailers must leverage data and advanced technology.

Customer 360

Knowing the customer comes through analyzing current company data as well as consumer and industry research. Most retail companies collect a great deal of customer data, but few realize how much knowledge is at hand and fewer still, how to leverage this data to create personalized experiences.

Retail data lives in many different systems, including marketing automation systems, web analytics, point-of-sale, customer relationship management, loyalty programs, and e-commerce platforms. With 40 percent of retailers claiming information lives in disparate systems, many retailers find it challenging to build a single view of the customer. In order to develop a unified understanding, information must be combined and organized. A definitive organizational data strategy is key to breaking down the silos of information, allowing data for easy access, sharing, and movement as needed.

Most retailers can make an educated guess as to the wants and needs of customers. However, without data to support assumptions — and discover new insights — personalization can only go so far. For example, a department store may assume a customer shopping online for dresses would be interested in dresses of a similar style as well as accessories and these suggestions could be worked into a recommendation engine.

However, when combined with data from other systems, the department store may discover the customer invested in fitness equipment six months ago and the dress is one of many garment purchases made in a smaller size. Health-focused offers may resonate better with this consumer than a pair of shoes.

With the applications of artificial intelligence and machine learning these insights and recommendations may be automated to deliver at scale. AI/ML also discovers hidden insights from mines of data. Advanced analytics may uncover purchase patterns across channels and time the delivery of offers or promotions to optimize the individual's shopping behavior.

Hyper-personalization also involves integrating new customer data points into the 360 view. Psychographic data can be collected to determine customer motivation. Knowing what compels the individual can help to determine what type of personalized experience a customer will value.

With the knowledge gained from internal data systems and automated psychographic research, retailers can create an analytics-driven approach that goes beyond conventional personalization. Using AI/ML, companies can apply advanced analytics to the customer journey in order to provide product recommendations or tailored-promotions at scale. With customer data ready and accessible, retailers must then find an enablement platform to deliver personalized experiences.

Delivering on personalization

Personalization means very little without a customer interface for content delivery. Content management system platforms such as SiteCore and Evergage, provide content management, digital marketing, and e-commerce capabilities designed to tailor the customer experience across channels. When systems are integrated, data can build on itself, allowing for customer engagement to be continuously optimized with real-time information gathered from cross-channel interactions.

Investing in content creation should be an essential part of most retailer's long-term strategy, but many retailers assume creating personalized content will be an onerous task. However, companies fail to realize personalization can start by leveraging the value of existing content. A CMS platform can customize content based on shoppers patterns of behavior. For instance, an e-commerce site like Amazon doesn't have a homepage, but each customer experience is individualized, based on what has been previously searched or purchased.

When selecting a CMS platform, it is first important to consider supported integrations. The flow of customer data to and from CRM databases, POS, AI/ML analytic applications, and other systems are essential to accessing customer intelligence to inform personalization. Retailers should also ensure the CMS has digital asset management and catalog management capabilities. DAMs help organize, manage and scale text, images, and rich media to deliver compelling experiences, while catalog management tracks and optimizes inventory across channels. Not all CMS platforms offer the inherent digital marketing management needed to push promotions offers via email, SMS and other digital channels, but most offer integration with marketing automation platforms such as Hubspot or Marketo.

Retailers will find a CMS that meets both needs and budget, as investing in such a platform is essential to a successful hyper-personalization strategy.

Conclusion  

In order to increase revenue and retain customer loyalty in the digital economy, retailers must create bespoke omnichannel experiences. Hyper-personalization leverages customer intelligence to drive engagement, create better brand experiences, and ultimately, drive loyalty and revenue.