Chapter 04
An integrated approach
How and why each step of a reimagined model works

01
Stage one
Pre-purchase
When data and insights are operationalized throughout the organization, tech support becomes a step on the path to purchase. For complex, premium, or professional- products and devices, one of the most effective ways to minimize the need for post-purchase support is to ensure the device aligns with the customer's initial needs and expectations.
By providing customers with access to experts during this stage — whether through phone, chat or co-browsing — brands can help bolster confidence in purchasing decisions. This approach not only decreases cart abandonment rates but may also enhance the likelihood of successful upselling and cross-selling.
Additionally, every customer interaction during this phase presents insights that can inform marketing and communication strategies, improve the information provided on websites and product descriptions, and enhance understanding of the potential and existing customer base in terms of their specific needs and expectations.
Case study
Using tech support agents to drive direct sales for a global consumer electronics company
As part of a wider CX delivery partnership for English- and German-speaking markets, Foundever provides B2C and B2B technical support services for a renowned multinational company that manufactures and sells both consumer and professional electronics devices.

02
Stage two
Segmented self-service
With a constantly evolving approach that incorporates new data and insights, self-service options can now cover a larger percentage of issues that would traditionally require agent assistance. This enhancement is not solely due to adding more self-service content; rather, it comes from that content being better tailored to resonate with different customer demographics.
The vocabulary used to describe problems and solutions, along with the formats in which this information is presented — such as images, videos, diagrams or traditional text — must align with the varying preferences customers have for learning and information absorption.
Different demographic groups not only exhibit distinct preferences for communication channels but also often use unique vocabularies when articulating issues or understanding resolution steps. Advances in generative AI now enable organizations of all sizes to apply speech and text analytics and identify these variations easily, allowing for improved agent coaching and training as well as enhanced agent-facing resources. Additionally, these linguistic insights should be integrated into self-service functionality so that a larger cohort of customers can solve their own issues.
Case study
Using self-service to address demographic differences
As console gaming grows in popularity, so does confusion among parents. While it’s typically their children that play games, it’s the parents who pay for games, must fix technical issues, and are responsible for setting up permissions and parameters. So, how do you give parents confidence not just about their choice of console but in handling technical issues and managing how their families use the device?

03
Stage three
Automated assistance
This access to customer data and insights means organizations can develop and refine chatbots and voicebots that cater specifically to demographic needs and channel preferences and bridge the gap between self-service and agent support. Rather than simply answering FAQs, these automated solutions can engage in meaningful conversations and gather additional information and context about the customer’s situation. This nuanced approach allows these automated systems to address a substantial range of potential tier 1 issues, thereby reducing the volume of live contacts.
Moreover, when faced with complex questions or situations, these intelligent assistants can assess the information collected and seamlessly transfer the customer — and all relevant details — directly to the appropriate support tier. This ensures that inquiries are handled by the most suitable agent, leading to faster resolutions and a more efficient customer journey.
04
Stage four
Live support
With intelligent automation effectively managing straightforward inquiries and accurately triaging more complex issues, live support can be optimized, allowing resources to be deployed more strategically. As chatbots and voicebots handle initial assessments, tier 1 agents are freed from routine tasks, enabling a greater number of agents to be available for customer interactions. This increased availability ensures that experts remain accessible to assist customers navigating the pre-purchase stage, where personalized guidance is crucial.
Using analytics and automation to capture data and insights, streamline support, reduce live contact volumes and simplify tasks such as information retrieval fosters a better balance in team workloads. Qualified agents can focus on complex issues where their knowledge makes a difference, and this allows organizations to maintain high service levels and set more ambitious targets in relation to CSAT and NPS.