As we begin 2025, businesses are navigating a dynamic landscape shaped by evolving customer expectations, technological advancements, and a data-driven ethos. For HR, Marketing and Customer Experience leaders, staying ahead requires embracing trends that redefine how they empower people, analyze markets, and understand customers. Sarid Research Institute has identified the top five research trends shaping 2025—trends that will help organizations sharpen their competitive edge and make smarter, faster decisions.
Trend #1: AI Solutions – Specifically LLMs
It’s not surprising that the first trend to mention is AI, but we focus here specifically on large language models (LLMs). LLMs are revolutionizing how organizations operate. From streamlining recruitment processes for HR to enhancing customer journeys via chatbots for service and support teams, AI adoption is accelerating. By 2025, most software solutions will feature AI integration, however, at varying levels of success. For an AI solution to be successful it has to be useful (e.g., accurate and relevant), and seamless to operate (short response time, or even background work). Here are a few examples on how HR, CMOs, and CX leaders can leverage LLM capabilities:
- In HR
- Talent Matching: LLMs can be utilized to match candidates to job openings more effectively by analyzing skills, experiences, and preferences, ensuring a better fit for both the candidate and the organization.
- Automating Interview Summaries: AI can transcribe and summarize interviews, highlighting key points and providing structured feedback for hiring managers.
- Employee Retention Insights: By analyzing employee feedback and engagement surveys, LLMs can identify trends and suggest actionable insights to improve retention and workplace satisfaction.
- In marketing
- Audience Personalization: LLMs can create hyper-personalized content for different customer segments, tailoring messages to resonate with specific demographics or psychographics.
- A/B Testing Enhancement: AI can suggest multiple variations of marketing materials and predict which will perform best based on historical data and customer preferences.
- Trend Analysis: LLMs can scan large volumes of social media and industry news to identify emerging trends, helping marketers stay ahead of the curve.
- Campaign Optimization: AI can analyze past campaign performance and suggest adjustments in messaging, timing, and channel strategy to maximize ROI.
- In customer experience
- Personalized Support: LLMs can analyze customer profiles and interaction histories to provide tailored responses, improving satisfaction and building stronger relationships.
- Real-Time Sentiment Analysis: AI can assess the tone and sentiment of customer interactions in real time, allowing teams to intervene proactively in challenging situations.
- Enhanced Self-Service Options: LLMs can power intelligent self-service tools, such as chatbots and virtual assistants, capable of resolving a wider range of customer queries with minimal human intervention.
- Proactive Engagement: AI can identify potential customer needs or issues before they arise, enabling companies to deliver proactive support and create a more seamless customer journey.
- Insights from Feedback: By analyzing customer reviews and survey data, LLMs can uncover actionable insights, helping businesses refine products, services, and processes.
Trend #2: Data Science as a Key Component of Quantitative Research
Organizations are embracing DIY survey tools and straightforward data collection methods, making basic data gathering accessible to all. However, as these tools become widespread and their outputs commoditized, the demand for advanced analytics and expert guidance is rising. Data science is no longer just a technical skill—it is a strategic enabler that turns raw data into actionable insights through advanced methodologies, cutting-edge algorithms, and rigorous evaluation techniques.
Practical Application Examples:
- Advanced Segmentation in HR: Analyze employee satisfaction surveys using clustering algorithms to identify subgroups with unique needs or concerns, enabling tailored initiatives for retention and engagement.
- Market Segmentation for Marketing: Use quantitative techniques to uncover nuanced customer segments, allowing for hyper-targeted messaging, better positioning, and more effective marketing strategies.
- Predictive Analytics for CX and HR: Implement models that forecast customer churn or employee turnover, enabling proactive interventions and optimized retention strategies.
- Evaluation of AI and ML Model Performance: Apply rigorous statistical methods to assess model accuracy and ROI in real-world business scenarios, ensuring alignment with organizational goals and strategies.
In an era where data collection is increasingly democratized, the true differentiator lies in how organizations analyze and act on the data they gather. Data science transforms raw data into strategic insights, enabling businesses to predict trends, personalize experiences, and optimize operations. By embracing advanced analytics and integrating data science as a core component of their decision-making processes, organizations can move beyond commoditized insights to achieve a competitive edge, driving growth and innovation in an ever-evolving market landscape.
Trend #3: Accessibility to Machine Learning Models as a Tool
The democratization of machine learning (ML) continues to transform how organizations operate, empowering medium to large enterprises to harness its potential for addressing unique business challenges. With the increasing availability of skilled data scientists and vast amounts of business data, ML is no longer reserved for tech giants—it is now a practical tool that organizations across industries can leverage for decision-making, automation, and innovation. This trend complements the broader role of data science as a cornerstone of quantitative research, offering actionable insights and personalized solutions.
Practical Application Examples:
- HR: Predictive analytics for employee retention. A custom ML model analyzes historical HR data, such as performance reviews, engagement survey results, and turnover patterns, to predict which employees are at risk of leaving. This allows HR teams to intervene proactively with retention strategies tailored to individual needs.
- Marketing: Dynamic ad targeting. A model trained on customer behavior and purchase history predicts the likelihood of specific segments responding to an ad campaign. This enables marketing teams to deliver highly targeted advertisements, improving click-through and conversion rates while optimizing ad spend.
- CX (Customer Experience): Real-time sentiment analysis. ML-powered tools assess the tone of customer interactions (via chat, email, or calls) in real time, flagging negative sentiment for immediate resolution. This ensures faster response times for dissatisfied customers and enhances overall satisfaction.
Trend #4: Agile Research: Fact-Based and Actionable
Agile research methodologies are transforming how organizations approach data-driven decision-making. Inspired by the iterative nature of software development, this approach involves breaking large-scale research initiatives into smaller, focused studies. This allows organizations to adapt quickly to changing conditions and derive actionable insights at every stage of the process. By emphasizing agility, businesses can ensure their research remains aligned with real-world objectives and immediate decision-making needs.
Benefits of Iterative Research:
- Faster Time-to-Insight: Iterative research enables quicker access to actionable insights, ensuring that decision-making aligns with fast-moving market dynamics.
- Real-Time Adaptability: Continuous feedback loops allow organizations to respond effectively to emerging trends, employee feedback, and customer needs, ensuring relevance and timeliness.
Practical implications:
- In HR:
- Pulse Surveys for Continuous Employee Engagement:
Traditional annual surveys often lag behind real-time workplace dynamics. By adopting iterative research methods such as frequent pulse surveys, HR teams can track employee sentiment, identify pain points, and implement timely interventions to boost morale and retention. - Proactive Workforce Planning:
Agile methodologies enable HR leaders to test and refine policies—such as hybrid work models or benefits programs—in short cycles, ensuring that changes are based on robust, real-world data rather than assumptions.
- Pulse Surveys for Continuous Employee Engagement:
- In Marketing:
- Incremental Campaign Testing:
Rather than committing to a full-scale marketing campaign upfront, iterative research allows marketers to test concepts, visuals, or messages on smaller audiences. Insights gathered from these tests inform adjustments that maximize impact before broader rollout. - Enhanced Brand Perception Analysis:
Regularly conducted brand sentiment analysis enables marketing teams to monitor how external factors—such as competitor activity or market shifts—affect consumer perceptions. This ensures strategies remain agile and responsive.
- Incremental Campaign Testing:
- In Customer Experience:
- Improved Service Designs:
By continuously collecting and analyzing customer feedback in iterative cycles, CX teams can refine service processes or digital interfaces incrementally, delivering better user experiences over time. - Real-Time Resolution Strategies:
Agile research facilitates faster testing of solutions for service bottlenecks. For example, CX teams can pilot different chat support models, track effectiveness in real time, and deploy the most successful one broadly.
- Improved Service Designs:
This trend also includes the Diversification of Deliverables
Research deliverables are no longer one-size-fits-all. Organizations now expect a tailored mix of outputs that cater to diverse stakeholders:
- Raw data for analytics teams.
- Processed data and insights for market research and business intelligence teams.
- Presentations for executive decision-makers and marketing professionals.
- Dashboards and visualizations for operational and managerial levels.
This flexibility ensures that insights are accessible, usable, actionable, and aligned with organizational goals.
Trend #5: Improved Integration of Data
Data integration is advancing rapidly, enabling businesses to combine internal and external data sources to uncover patterns and relationships that were previously hard to detect. By breaking down data silos, organizations can derive more holistic insights that drive impactful decisions across departments.
Examples of Integrated Insights:
- Correlations Between Employee Engagement and Customer Service Quality:
HR and CX teams can collaborate to analyze how engaged employees contribute to better customer experiences, identifying key drivers for improving both retention and satisfaction. - Marketing Mix Models (MMMs):
By integrating sales, advertising spend, and external market data, marketing teams can measure the true impact of campaigns on awareness, conversion rates, and overall KPIs.
Implications for Collaboration – This trend fosters more interdepartmental collaborations, such as:
- HR & CX: Joint initiatives to improve both employee engagement and service quality, leveraging integrated insights to design effective training programs or incentive structures.
- Marketing & Sales: Coordinating efforts to align marketing campaigns with sales data, ensuring that promotional strategies are tailored to maximize conversions.
- Finance & Marketing: Working together to optimize marketing spend by combining financial data with MMMs to measure ROI and allocate budgets more effectively.
- CX & Product Teams: Using integrated feedback from customers and product usage data to prioritize feature updates or new service offerings.
Conclusion: Staying Ahead of the Curve
To thrive in 2025, organizations must embrace these trends while ensuring their strategies are data-driven, innovative, and actionable. Human Resources, Marketing and Service leaders should adopt these tools to get more accurate results in a faster manner.
At Sarid Research Institute, we specialize in helping businesses harness these opportunities. From advanced data science services to tailored ML models, we’re here to guide your journey toward smarter decisions and stronger results.
Next Steps:
- Evaluate how your organization and department currently use AI and data science tools.
- Identify areas where custom solutions can amplify impact.
- Consult with us for advanced solutions designed to meet your unique challenges.
By staying informed and proactive, HR, Marketing and Service leaders can turn 2025 into a year of growth and innovation. Let’s shape the future together.