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Next-generation KPIs: Redefining customer experience measurement - Hero

Customer experience (CX) is evolving — and your measurement strategy should too. Discover how next-generation KPIs can offer deeper insight into CX performance, from customer effort and journey satisfaction to agent engagement and digital maturity.

Next-generation KPIs: Redefining customer experience measurement

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Access the latest survey results and stay on top of CX developments in 2025 with this new report by Execs In The Know, sponsored by TELUS Digital.

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Execs In The Know: 2025 CX Leaders Trends & Insights

Discover how TELUS Digital transformed customer support for a leading cryptocurrency platform, scaling the program within weeks while achieving high customer satisfaction scores.

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Reduction in Average Handle Time within 3 months

Reduction in Customer First Response Time

Elevating the customer experience for a leading cryptocurrency platform

Discover how TELUS Digital used our proven field operations testing (FOT) experience to create a high-quality dataset for training advanced driver assistance systems (ADAS) and autonomous vehicles (AV).

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Curating high-quality data for the training and validation of ADAS and AV models

Discover the importance of data neutrality in today’s AI ecosystem, and why partnering with an ethical, trust worthy and impartial data provider has never been more important.

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Why data neutrality is more critical than ever

Join industry experts from TELUS Digital and Everest Group as they explore how leading technologies, such as generative AI, automation, analytics and more, are delivering value for organizations without compromising service quality.

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Efficient CX delivery: A tech-driven approach

As the telecom industry faces mounting costs and shifting customer expectations, AI can turn challenges into opportunities. Learn more about the use cases.

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How telecom brands can seize industry opportunities with AI

Jim Mitchell

This article was originally published on ExecsInTheKnow.com as part of our Outsourcing Briefing series.

Right now, economic pressures are pushing customer experience (CX) leaders and their outsourcing providers to get creative in finding solutions that heighten efficiency without lowering service quality. Once again we’re reminded that necessity is the mother of all invention.

In my role as vice president of customer experience and digital innovation at TELUS Digital, I’ve been having conversations with CX leaders that follow a similar pattern. They’re grappling with rising customer expectations for efficient service, increasing operational costs and shifting talent requirements for agents due to improvements in self-service solutions. Ultimately, these leaders are looking for value and are adamant that the choices they make are going to need to stand up to significant scrutiny.

It’s my estimation that, due to a combination of factors, the business process outsourcing (BPO) industry is on the precipice of a considerable evolution. In fact, if you just look at the projected growth of the BPO market, it’s expected to scale to $525.23 billion by 2030, growing at a CAGR of 9.8% from 2025 to 2030 according to Grand View Research. Beyond the scale, this is a time of great change and possibility. A host of agent-facing technologies are augmenting the abilities of contact center professionals, opening up new compelling outsourcing opportunities around the globe. Where once a brand might have only considered delivering support from onshore sites, they’re now looking offshore. Where once a brand might have limited their scope to a few countries, they’re beginning to recognize a world of opportunities.

The leaders I’ve been speaking with are interested in exploring new payment models. They’re looking to performance-based pricing models, which create shared accountability and strengthen partnerships between brands and their BPO providers. These new pricing models, coupled with new technology, are reshaping CX delivery in a cost-conscious world.

Why outsourcing models are being reimagined

While cost pressures are driving many conversations right now, what’s fascinating is the ways in which these forces are pushing the industry to evolve beyond simple cost-cutting. What I’m seeing instead is a push toward balanced value creation, where organizations are finding ways to optimize costs while building strategic partnerships that drive innovation and enhance customer lifetime value.

This evolution is particularly evident in how contact centers are being leveraged. As industry expert Adrian Swinscoe recently noted on an episode of the TELUS Digital podcast, Questions for now, “The contact center is this gold mine of real-time data, which many brands are not really leveraging to its full extent.” Forward-thinking organizations are now treating their contact centers as strategic assets, increasingly working with their CX partners to derive insights and ultimately improve products, enhance service delivery and drive customer loyalty.

This shift towards strategic partnerships is reshaping how brands approach outsourcing altogether. We’re witnessing a growing number of countries emerge as viable outsourcing locations, which is enabling brands to dilute risk across numerous regions and sites, offer support across time zones and leverage specialized expertise. By thoughtfully matching customer needs with these varied talent pools, brands can optimize their CX delivery. For example, this could mean routing complex technical issues to specialized teams, ensuring language-specific support is available or tapping into local cultural knowledge for more nuanced customer interactions. The result is a more flexible, resilient and capable global CX operation that can adapt to changing customer demands while managing costs effectively.  TELUS Digital has more than 30 countries of operation, setting us up to match the right capabilities with each brand’s unique needs, whether that’s multilingual support, follow-the-sun coverage or specific domain knowledge.

The result is a more sophisticated approach to outsourcing that goes beyond simple labor arbitrage. It’s about leaning on a partner to find the right balance between cost efficiency and value creation, recognizing that the cheapest option isn’t always the most cost-effective in the long run.

The proliferation of AI in the contact center is erasing traditional limitations and creating opportunities for exceptional service delivery from anywhere in the world. According to HubSpot, 78% of customer service professionals report that AI and automation allow them to concentrate on the most important aspects of their roles. Think of what that could do to reduce stress for agents and minimize attrition, which as all CX leaders know, is a significant cost in the industry. In a separate study from Microsoft about enterprise use of AI in general, it was found that for every $1 invested in AI, companies are seeing a $3.50 return — often in just 14 months.

At the heart of this transformation are AI-powered knowledge bases and systems that put the collective wisdom of an entire organization at every agent’s fingertips. I once had a really eye-opening experience at a logistics company’s in-house contact center. In the middle of a side-by-side, an agent pulled open a desk drawer and referred to a printed FAQ document. I knew that wasn’t permitted, and when I asked him about it after the call, he explained that their knowledge base was so vast that it was impossible to find what you were looking for. He said, “We just have learned to adapt so we can take care of the customer experience.”

We helped this client out by deploying speech analytics to identify the most frequent reasons for support calls, narrowed it down to about 50 knowledge base articles, which comprised about 90% of the call volume. Next, we summarized those articles, worked on a knowledge base chatbot fueled by AI, and almost immediately we saw a dramatic change. The solution reduced average handle time by 38 seconds while increasing CSAT by nine points, but most importantly, it boosted agent confidence and satisfaction — particularly among new hires — leading to lower attrition rates.

Beyond knowledge management, we’re seeing remarkable advances in other areas that are transforming global CX delivery. Real-time coaching and performance analytics provide instant feedback, helping teams continuously improve their skills. Collaborative platforms narrow the distance between contact center locations, enabling the delivery of consistent customer experiences. Through AI-driven routing and task allocation, savvy leaders are matching customer needs with the right expertise, improving first-contact resolution rates.

Similarly, speech enhancement technology increases call clarity for phone support. Background noise, poor connections and other technical barriers can create friction in support interactions. The technology works by processing audio inputs in real time, filtering out background noise, enhancing voice clarity and optimizing sound quality — much like how noise-canceling headphones improve listening experiences. With this technology, brands can ensure clear conversations between customers and agents, preserving the authentic voice and personality of agents while optimizing for mutual understanding.

Outcome-based pricing aligns incentives between partners

To navigate cost pressures, the leaders I'm speaking with are increasingly looking beyond traditional pricing models, and instead want to explore a dynamic where compensation is tied directly to results. This outcome-based approach creates natural alignment between brands and their outsourcing partners, as both parties are invested in achieving the same goals. It’s a model that gives brands confidence to expand their geographic horizons, knowing their partners are equally invested in delivering excellence through clearly defined, measurable outcomes. It bears repeating that this type of pricing strategy, in conjunction with speech enhancement and language translation technology for non-voice support, is having a marked influence on how leaders are looking at CX delivery right now. Those who would never even have considered looking to leverage support from beyond their shores are now moving on international opportunities.

The beauty of outcome-based pricing is its flexibility. For sales-focused programs, we might tie compensation to conversion rates or revenue generated. In customer care scenarios, we could look at metrics like customer satisfaction scores or first-call resolution rates. Some brands might prioritize efficiency metrics like reduced handle times, while others focus on customer loyalty indicators. On the other hand, forward thinking leaders and boundary pushing companies may go even further, tying compensation directly to specific outcomes achieved, such as total monthly paid/active subscribers or completed transactions, moving completely away from measured KPI reliant pricing models. The key is choosing outcomes that genuinely reflect the value being created and working with a partner who is able to deliver.

Clear agreements, with well-defined metrics and measurement methodologies, are essential. Both parties need a shared understanding of what success looks like and how it will be measured. This includes establishing baseline performance levels, defining measurement periods and agreeing on how external factors might impact outcomes.

When done right, this model transforms the brand-provider relationship from a transactional one to a true strategic partnership. It encourages innovation, as providers are incentivized to find new ways to improve performance. What’s more, it fosters a long-term perspective, as both parties focus on sustained success rather than short-term gains.

Adapt proactively to changes in the CX landscape

The customer experience outsourcing landscape is in a state of flux, driven by technological innovation and evolving partnership models. AI-powered tools are enabling contact center teams to deliver exceptional service from anywhere in the world, while outcome-based pricing models are creating stronger alignment between brands and their CX partners.

What excites me most about this evolution is how it’s changing the conversation. Where once the focus might have been solely on cost reduction, today we’re talking about value creation. We’re discussing how to leverage global expertise, enhance service quality and drive innovation — all while maintaining cost efficiency. The most successful brands will be those that embrace and adapt to these changes, working with partners who can help them navigate this new landscape.

If you’re ready to explore how these approaches could benefit your CX operations, connect with our team of experts.

Explore new CX outsourcing opportunities in this article by Jim Mitchell, vice president of customer experience and digital innovation at TELUS Digital.

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Transform your customer experience

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Explore trust and safety trends for 2025 from a survey of 819 enterprise leaders. Gain insights on fraud detection, KYC, content moderation and ID verification.

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Join Steve Nemzer, director of AI growth and innovation for TELUS Digital, as he unveils the transformative world of agentic artificial intelligence (AI). Learn what makes AI “agentic”, various use cases and implementation best practices to benefit your organization.

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 Are you ready for the era of agentic AI?

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On this episode, we explore strategies that transform customer experience into a revenue engine — and how to communicate CX wins with language that resonates with C-suite executives.

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Unlock AI ROI with proven delivery leadership strategies. Learn how to reduce costs, drive value, and transform skeptics into champions.

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Stop wasting AI investment: How delivery leadership can slash costs and drive ROI

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Magna 3D after EMC

High-density Point Cloud

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3D polylines

Mapping data is essential for the automotive navigation ecosystem as it enables autonomous vehicles (AV) and advanced driver assistance systems (ADAS) to understand four critical things: where it is, what surrounds it, where it’s headed and the best path to get there.

Mapping requires creating digital representations of the road environment to support safe and efficient driving. In contrast to traditional navigation maps, modern automotive maps feature precise lane-level detail and rich semantic information, such as lane boundaries, road markings, signs and intersection geometry. By providing detailed, precise and centimeter-level accurate digital representations of the road environment, digital maps offer vehicles a human-like context that enhances what their sensors perceive, essentially building a rich, 3D view of the world around them.

These maps are critical for a range of vehicle functions, including:

Augmenting sensor capabilities to see beyond perception systems, with existing maps and recorded features to assist extraction of information, surpassing real-time detection, especially in adverse weather and obstructed visibility conditions.

Better localization through the use of onboard sensors combined with mapped features instead of relying on the global positioning system (GPS) alone.

Improved path planning with information on lane connectivity, traffic rules and road geometry to make safer decisions in complex scenarios like intersections or merges.

Three critical stages for mapping annotation

Since mapping plays a critical role in how vehicles understand and navigate their surroundings, building accurate context via annotations requires a structured, multi-step process. There are three key stages in this process that require careful attention and specialized expertise. Let’s walk though these steps on Ground Truth Studio (GTS), our proprietary annotation platform.

Step 1: Raw data transformation and pre-processing

Once raw data is collected, global navigation satellite system (GNSS) and inertial measurement unit (IMU) measurements are used to estimate the vehicle’s position and orientation over time. Using this data, sensor outputs such as lidar point clouds and images are transformed from the ego-vehicle coordinate frame into a common world reference frame to ensure spatial consistency.

For lidar data captured as timestamped frames, each frame is aligned using ego-motion data to account for the vehicle’s movement.

The processed point cloud and corresponding imagery are spatially and geometrically aligned, enabling accurate interpretation of map features. Multiple aligned consecutive frames are combined to generate an aggregated point cloud (APC), forming a unified spatial view of the environment.

The aggregated point clouds or keyframes need to be enhanced using the following methods:

Environmental and sensor-induced noise is removed using in-house filtering algorithms to improve clarity and accuracy.

The detection and removal of dynamic objects such as vehicles and pedestrians, isolating static features necessary for mapping.

Aggregated frames may contain motion blur due to vehicle movement. Using ego motion compensation (EMC) algorithms can correct such distortions, ensuring sharper, more reliable point clouds.

Step 2: Loading high-density point clouds

For making/editing and Quality Control (QC) workflows, Ground Truth Studio supports tens of millions of high-density point clouds, allowing teams to work with detailed spatial data without performance compromise.

Optionally, in-house smart downsampling algorithms can be used to label strategic frames, ensuring a smoother annotation experience for huge point clouds when needed. These algorithms optimize point density by preserving high-resolution details like road markings, in critical regions, while downsampling less relevant areas like, for example, vegetation.

Given the complexity and precision required in automotive maps, the annotation process is a vital step in ensuring the final output meets accuracy standards for autonomous or assisted driving applications. To manage the scale of mapping large geographic areas, data is segmented into smaller, more manageable units known as map tiles. Each tile contains:

Associated imagery (from multiple RGB or grayscale cameras)

Calibration metadata for multi-sensor alignment

Pose and timestamp data to enable spatial-temporal validation

Once the tile is set up, annotators create vector representations of real-world features, primarily using 3D polylines and 3D cuboids:

3D polylines are used for road boundaries, lane lines, crosswalks, curb edges and stop lines

3D cuboids may represent traffic signs, poles, signal lights or physical obstacles

Each geometric annotation can then be enriched with attributes, which help define the semantics of a feature, for instance, speed limits or the type of traffic sign. After all map tiles are fully annotated and validated, they are stitched together to form a seamless automotive map.

Key features for 3D polyline annotation platforms on Ground Truth Studio

A full-featured annotation platform, as well as expert annotators trained in mapping, play a significant role in accurate mapping annotations. Smart features are a huge part of ensuring this accuracy with operational efficiency.

Ground Truth Studio offers comprehensive support for automotive mapping, including advanced features to enhance productivity and quality. Using our tool, annotators can create precise 3D polylines and 3D cuboids directly on the point cloud. The platform supports automatic 2D projections on camera images using calibration data if users need to view 2D projections for both cuboid and polyline annotations. For dedicated 2D annotations, our sensor fusion tool enables 2D polyline, rectangle creation and 3D-2D annotation linking across sensor modalities.

Ground Truth Studio offers a wide range of attribute configurations such as single or multi-select and text input for accurate metadata annotation

Parent-child linking (Hierarchical): Used when one annotation depends on another.

Two-way linking (Non-hierarchical): Used for representing peer-to-peer relationships where elements are connected but not strictly dependent in a hierarchical sense. (e.g., linking a virtual lane class (VLC) to associated lane lines).

Each link can include a property, such as specifying if a lane line is on the left or right of a VLC.

To significantly enhance the efficiency, accuracy and ease of use for annotators working with 3D data, our platform is built with a suite of productivity features specifically designed to streamline the 3D polyline annotation workflow.

Automated ground anchoring with ML-generated meshes

Manually setting the height (Z-value) for each point in a 3D polyline can be tedious and error-prone, particularly when working with complex terrain or large datasets. To simplify this, our platform uses machine learning-generated hybrid ground meshes as anchor surfaces. The first annotation made by an annotator automatically snaps to the ground, reducing the need for manual height adjustments and improving both speed and precision.

Our axis locking tools help maintain geometric accuracy by allowing annotators to lock lines to specific orientations, perfectly vertical (Z-axis lock) or horizontal (XY-plane lock). This feature prevents accidental deviations and ensures cleaner, more reliable annotations, eliminating the need for constant manual corrections.

Many real-world road environments contain repetitive structures like parking spaces, building edges and road markings are common. Instead of re-annotating from scratch, our platform allows annotators to duplicate existing polylines and make fine adjustments to individual points. This saves significant time while preserving accuracy.

Line direction visualization and line connection

To provide immediate clarity on the flow or intended direction of an annotation and to connect two 3D polyline annotations to form continuous paths or networks, our platform includes line direction visualization and line connection respectively. This intuitive visual feedback enhances understanding and reduces errors in path-based annotations.

Scaling mapping annotations through partnership

Automotive maps, especially semantic maps enriched with geospatial data, provide the critical context autonomous systems need to make safe, confident decisions on the road. They enhance perception, enable smarter path planning and support scalable operations by helping autonomous systems anticipate road conditions and traffic scenarios.

In contrast, choosing a mapless approach shifts the entire burden of navigation and safety onto real-time systems. This creates several significant challenges:

Your vehicle must constantly process large volumes of raw sensor data, demanding costly and complex onboard hardware

Without prior map knowledge, rare or unpredictable scenarios become harder to handle safely

Proving the safety and reliability of a mapless system across an infinite variety of real-world scenarios is a significant regulatory and engineering challenge

Handling the operational demands of large-scale mapping projects can be highly complex, where efficiency plays a crucial role.

At TELUS Digital, we make mapping scalable and cost-effective. Backed by our team of expert annotators, we combine advanced tools with deep domain knowledge to deliver exceptional accuracy at scale. With tile-based collaboration, smart productivity features and intuitive UX, Ground Truth Studio enables seamless, conflict-free contributions from multiple users working in parallel.

Where are you on your mapping journey? Connect with our experts at TELUS Digital today to review your current approach and consult on the best next steps to help you build safer, smarter autonomous vehicles.

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