Tell us about your role and the team/technology you handle at Sitel Group.

As the VP of Analytics and Client Insights, I lead a team of Data Experts responsible for the development and execution of data-driven campaigns to improve the customer journey. Leveraging deep contact center data derived from every touchpoint on the customer journey, I get under the hood of customer experience (CX) programs to better understand client challenges, successes, and areas for growth opportunities.

At Sitel Group, which technologies drive your Contact Center and Customer Experience?

Sitel Group has used CallMiner’s Analyze and Coach technology to provide actionable insights that improve efficiency and customer satisfaction. The technology has helped achieve these results by providing understandable data insights from every contact center call and identifying which agents the coaches should focus on improving most. CallMiner’s technology has allowed Sitel to transform agent performance through Data Analytics and therefore improve customer experiences for their clients.

We also use NICE inContact’s CXone suite to provide our various locations with Omnichannel routing for voice, chat and email all on one platform. It helps us cut down on time for external transfers between agents and makes a faster and better experience for the customer.

What is the current definition of Marketing Analytics for digital campaigns?

Marketing Analytics is how we analyze the key data points for a campaign and come up with outcomes to improve our strategy moving forward. There are many important aspects of Marketing Analytics for digital campaigns, but first and foremost, organizations must make sure that they are measuring the right data. They need to uncover and capture the right data sets to analyze their goals and objectives and therefore create improvement for future campaigns. If you’re not measuring the right data you won’t be successful. Throughout the campaign, it’s critical to continue reevaluating the data you’re measuring and make adjustments accordingly. Finally, once it’s time to analyze the data, organizations must ensure they are looking at this data tactically to see what has been successful and what areas need improvement.

How can an organization build a successful Contact Center?

A successful contact center comes down to the people working there and the training and coaching the company provides. At Sitel Group, we integrate technology that helps us analyze 100% of customer interactions and use real-time analytics to help understand where the agent needs additional coaching and training. Analyzing customer interactions also help the brands we work with improve their strategy. With this, we can identify what points in the customer journey are creating the most frustration or difficulty for consumers and provide solutions that help improve the path to purchase and beyond.

How are BPOs evolving with MarTech and Salestech tools?

Overall the industry is becoming more and more data-driven. As we discussed, the technology available to us today helps us create better customer service agents, and therefore create better service for consumers, making brands look their best as well. Customer service has become a stand out factor in consumer satisfaction and retention. With new Technology and Data Analytics, we’re now able to target specific areas of the journey to decrease customer churn, increase efficiency in the customer service process, drive loyalty and even boost Sales.

How can marketers leverage AI ML and Data Science to achieve benchmark CX goals?

A recent survey Sitel Group conducted found that nearly all employees believe that the employee experience impacts CX, so when looking to achieve benchmark CX goals it really starts with employees. Customer service agents’ jobs are not easy, often dealing with frustrated or angry customers, so it’s essential that companies provide their employees with the training needed to make them the best agents and provide them with the confidence that creates a better employee experience. Using Data Science and AI, we’re able to better understand customer interactions and identify trends. One area that this is particularly useful is in measuring sentiment. AI can pick up on certain keywords and phrases for different customer emotions. Monitoring and analyzing those trends are key to improving customer service and therefore achieving CX goals.

What are the challenges in fully maximizing media performance across digital platforms?

There are so many different platforms, with new technologies invented nearly every day, so one of the biggest challenges for many organizations is keeping up and ensuring they are targeting the correct audience on the correct platforms. For example, Gen Zs may be more interested in using a chatbot or a chat function on a website, while Gen Xs may prefer to email in their questions. This is why data is so important – knowing your audience is critical and Data Analytics can help identify trends and sectors that help ensure digital platforms are used in the way that best matches the needs of the different audience segments.

What does it take for an organization to build true Customer Intelligence?

Looking at customer interactions it one of the most important aspects of building true Customer Intelligence. At Sitel, we leverage 100% of customer interactions to gain the best possible data to inform our clients about trends and challenges with their target customers. Looking at every channel from email to chat to phone calls is needed to gain a real picture of the customer and understand their needs.

How do you differentiate between various data points- Audience, Customer, Intent, Sentiment, and Big Data?

Audience is the segment of consumers that our client is trying to reach – this is absolutely one of the most important pieces of data brands and organizations need in order to put a strategy in place, as it sets the tone for the rest of the data points. Customer data refers to the actual individuals buying or interested in our clients’ products. These are the consumers that we can work to best understand as our agents interact with them on a daily basis. Intent data is similar to engagement, it’s a critical piece of understanding what makes customers buy a product, or lose loyalty in a brand.

Sentiment refers to data related to emotions – it can measure anger, professionalism, frustration, and so much more. This data is particularly useful in gauging how employees should react and providing better coaching experiences.  All of these areas feed into Big Data – the larger data sets that we use to identify overall trends and challenges and create recommendations to increase brand loyalty, reduce churn, expedite the path to purchase, etc.

What are your predictions about your market/customer base in the next 3 years?

Although it is already a major component in Data Analytics, I believe we’ll continue to see AI and predictive analytics play a larger and larger role in the industry. As AI continues to get smarter there will be so many additional applications within the customer service industry and in analyzing the data itself. With the increase in AI and Predictive Analytics we’ll also need to invest in the growth of more Data Scientists – while the intelligence aspect of AI is getting smarter, we’ll still need the human touch to really get to the bottom line of the data and understand how to create initiatives to improve areas spanning from predictive modeling to data presentation.