Partners + Programs

Retail Technology Solutions

At the heart of the retail industry’s digital transition is Retail Technology.

RetailTech is complicated … it’s people, it’s places, it’s things, and the intersection of all of them. Retail technologies frequently leverage the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML). These innovative technologies have ushered in the age of Big Data, creating endless amounts of data, forcing companies to design and adopt solutions that are flexible and can scale. When designed smartly, these digital technologies can optimize essential aspects of the retail business and foster digital transformation and omnichannel customer experiences.

How we can help retailers:

Where we can start

We work with the world’s leading technology solution providers. In partnership with these cutting-edge tech companies, we’ve designed a program to JumpStart your Customer, Technology, Data success.

Our JumpStart Retail partnership program fast-tracks business results and platform solutions. JumpStart enables organizations to enhance customer satisfaction through a data-driven approach, drive innovation through new technologies, and achieve competitive advantage.

Tailored to your needs, our user-centric approach, tech smarts, and collaboration with your stakeholders equip teams with the skills and mindset needed to:

  • Identify unmet customer, employee, or business needs
  • Align on priorities
  • Rapidly prototype solutions
  • And fast-forward success

Contact us today to JumpStart your Retail Technology solutions. 

Team outlining ideas together on a clear board

“Current market volatility has hit retailers hard. Many are struggling to re-orient operations to meet customer expectations.”

Forrester, Retail Trends

Retail Experiences + IoT Applications

Retailers are embracing IoT-enabled experiences that gather, process, and manage data to uniquely engage their customers. Forward-thinking retailers can leverage IoT and other retail tech applications to:

  • Increase customer satisfaction by reducing in-store friction to outperform the competition.
  • Empower customers to engage with in-store content, while also boosting their experience.
  • Foster tech-enabled innovation to improve in-store digital experiences by understanding customer traffic patterns and how customers engage with the retailer’s products and experiences.

Kopius enables smart IoT solutions to help retailers become more informed about their customer experiences.

Retail Experiences + IoT Application Technologies

Instore Operations + Analytics

Build a more connected retail environment by implementing smart retail tech applications, including IoT, AI, and ML. There’s no need to fund all new tech aspects at once, prioritize a phased approach to accelerate new tech solutions assisting store operations and empowering the front-line workers to focus on the customer services that matter most:

  • Make retail operations more efficient.
  • Evolve operating models to positively impact business strategy, execution, and advance business operations.
  • Extend sales channels to seamless, multi-channel experiences.
  • Collect and analyze consumer preferences and behavior data, leveling the competition from brick-and-mortar to online retail merchants.
  • Match consumer expectations for convenience, immersive shopping, safety, and speed by enabling personalized consumer data recommendations and retail promotions.

Kopius helps retailers enhance productivity across the workforce by streamlining technologies, data, and processes.

Retail technology

According to Retail Customer Experience, “Retailers are expected to have 70% of routine tasks automated by 2025 and are prioritizing tech investments that will boost operational efficiency which will lead to reduced costs and higher profits.”

Instore Operations + Analytics Technologies

“Customer opinion is a major driving force for retailers to adopt new technology. As consumer preferences shift, retailers will invest in new technologies to keep up with changing demands.”

Gartner Reports

Retail CDP + Personalized Marketing

Simplify the complexity of collecting and managing customer data. Experience how a single retail search can activate personalized consumer algorithms that will trigger real-time product recommendations, email notifications, push notifications, loyalty messaging, dynamic pricing, landing pages, service chatbots, and transition your one-time customer into a repeat customer.

Hyper-personalize your customer experience, by activating your customer data efficiently & securely:

  • Process large scales of data, including consumer, transactional, social, and competitive data, and provide significantly useful insights to your business through modern technologies, like predictive inferencing and machine learning algorithms.
  • Strengthen your retail sites and shopper data protection.
  • Hyper-personalize an omnichannel customer service experience.
  • Design and build a CDP that is agile and smart enough to handle frequent changes needed both at scale and speed.

Kopius helps retail organizations activate customer data to hyper-personalize customer experiences.

Retail CDP + Personalized Marketing Technologies

Data + Security

Solve key retail technology implementation challenges by designing for data security, infrastructure, and governance.

  • Petabytes of data created by IoT has ushered in the age of Big Data, as the retail industry evolves, adopt secure data solutions that are flexible and can scale to handle the increasing data load.
  • Modernize your IT infrastructure to support your RetailTech investments and better meet the fast-paced demands of your business and customers to raise the bottom line.
  • Prioritize your data security investments to reduce breaches.

Kopius helps retail organizations activate customer data to hyper-personalize customer experiences.

According to Gartner, “Today’s data management best practices are largely unable to cope with the complexity, distribution, and pace of data in modern digital business. Data and analytics leaders should stop striving for total data control and instead adopt a flexible, adaptive approach to data management.”