Learning Objectives

By the end of this chapter, you will be able to:

  • Define Marketing Technology (MarTech) and describe a typical MarTech stack.
  • Explain how web transaction logs, cookies, and tracking pixels collect customer data.
  • Describe the role of web analytics and the main metrics it reports.
  • Explain databases, data warehouses, data mining, and big data in marketing.
  • Understand how CRM and marketing automation platforms are used in marketing.
  • Explain personalization, recommendation engines, and programmatic advertising.

Marketing Technologies (MarTech)

Marketing Technology, or MarTech, is the range of software and tools that marketers use to plan, execute, and measure their campaigns. Together these tools form a MarTech stack: data flows in from the website, app, and campaigns; it is stored and analysed; and it is used to send the right message to the right customer.

flowchart TD
    SITE[E-commerce Website] --> WA[Web Analytics]
    SITE --> CRM[CRM System]
    CRM --> MA[Marketing Automation]
    MA --> CH[Channels: Email, Social, SMS]
    WA --> PERS[Personalization Engine]
    CRM --> PERS
    PERS --> SITE

Figure 1: Marketing Technology Stack

1. How Customer Data Is Collected

Technology What it records
Web transaction logs Every request a server receives: pages viewed, time, IP address, browser, referrer
First-party cookies Set by the site you are visiting: login, cart contents, preferences
Third-party cookies Set by other companies (ad networks) to follow users across many sites
Tracking pixels (web beacons) Tiny invisible images or scripts in pages and emails that report when they are loaded or opened
Mobile device IDs and app SDKs Identify a phone and record in-app activity and, with permission, location
Forms and purchases Data customers give directly: name, phone, address, order history

Browsers are phasing out or restricting third-party cookies, and privacy laws require consent, so firms rely more on first-party data: information customers share directly with the business.

2. Web Analytics

Web analytics is the measurement, collection, analysis, and reporting of web data to understand and improve a website. Tools such as Google Analytics show where visitors come from, what they do, and whether they buy.

Metric Meaning
Users and sessions How many people visited and how many visits they made
Traffic source Search, social, email, paid ads, direct, referral
Bounce or engagement rate Share of visits that leave at once vs. interact
Pages per session, time on site Depth of interest
Conversion rate Orders (or sign-ups) ÷ sessions × 100
Cart abandonment rate Carts not completed ÷ carts created × 100

3. Databases, Data Warehouses, and Data Mining

  • A customer database stores records of customers and their transactions.
  • A data warehouse combines data from many sources (website, app, shop tills, CRM) into one store designed for analysis rather than daily transactions.
  • Data mining finds patterns in that data:
    • Query-driven: answering specific questions (“Which district bought the most rain jackets in July?”).
    • Model-driven: building models to predict behaviour, such as which customers are likely to stop buying.
    • Rule-based: applying rules, such as “if a customer buys a phone, show cases and chargers”.
    • Collaborative filtering: recommending products that similar customers bought (“customers who bought this also bought…”).
  • Big data refers to very large, fast, and varied data (clicks, searches, videos, location) that needs special tools such as cloud data platforms to store and analyse.

4. CRM (Customer Relationship Management)

A CRM system is a database of every interaction a firm has with each customer, across all touchpoints: website, app, phone calls, store visits, social messages, and service requests. It gives a 360-degree view of the customer. Marketers use CRM data to segment customers (for example, “bought twice in the last 90 days, lives in Pokhara”) and to plan campaigns for each segment.

5. Marketing Automation

Marketing automation software runs repetitive marketing tasks automatically, based on rules and triggers. Common uses are welcome emails, birthday offers, abandoned-cart reminders, re-engagement messages, and scheduled social posts.

Worked example: an abandoned-cart flow

An online shoe store in Kathmandu sees 400 abandoned carts in a month. It sets up an automated reminder for customers who have agreed to receive messages.

  • Customers with consent who receive the reminder: 300
  • Open rate 40% → 120 opens
  • Click rate 25% of opens → 30 return to the cart
  • One third complete the purchase → 10 orders at an average of Rs. 3,000 = Rs. 30,000 in recovered sales

The flow cost a few hours to set up and a small monthly fee, and it runs every day without staff time. This is the main appeal of marketing automation: small improvements, repeated automatically.

6. Personalization and Recommendation Engines

Personalization uses data about a visitor — past purchases, browsing history, location, or segment — to show relevant content, products, or offers. Examples include product recommendations (“Customers also bought…”), dynamic email content by city, and returning visitors seeing their cart intact. Personalization improves conversion when it feels helpful, not creepy; it requires accurate data, privacy-aware consent, and tools such as CRM or marketing automation platforms linked to the website.

Recommendation engines use collaborative filtering and machine learning to choose which products to show each visitor. Large marketplaces such as Amazon and Daraz show different home pages to different users for this reason.

7. Programmatic Advertising

Programmatic advertising buys and sells ad space automatically. When a user opens a web page, an ad exchange runs an auction in milliseconds (real-time bidding): advertisers’ software bids based on what is known about the user, and the winning ad is shown. Ad networks such as Google’s display network and Meta’s audience network work this way. Programmatic ads are efficient and targeted, but they raise concerns about privacy, ads appearing on unsuitable sites, and fraudulent clicks from bots.

8. Privacy Concerns

The same tools that make marketing efficient also collect a great deal of personal data. Customers increasingly expect to know what is collected and to be able to say no. Good practice is to collect only what is needed, ask for consent, secure the data, and let customers unsubscribe easily. In Nepal, the Privacy Act, 2075 (2018) requires consent for collecting and using personal information.

Adoption of Marketing Technologies in Nepal

The adoption of marketing technologies by businesses in Nepal is still in its early stages. While many larger businesses are using a variety of marketing technologies, many smaller businesses are not.

Some of the most common marketing technologies that are being used by businesses in Nepal include:

  • Web Analytics: Web analytics tools like Google Analytics are being used by many businesses to track their website traffic and to understand how visitors are interacting with their website.
  • Social Media Management Tools: Social media management tools like Hootsuite and Buffer are being used by some businesses to manage their social media presence and to schedule their posts.
  • Email Marketing Tools: Email marketing tools like Mailchimp are being used by some businesses to send newsletters and promotional emails to their customers.
  • Bulk SMS and messaging: SMS gateways and messaging apps such as Viber and WhatsApp are widely used for order updates and offers, because many customers read messages more than email.
  • CRM (Customer Relationship Management): The use of CRM systems is still not very common in Nepal, especially among small businesses. However, some larger businesses are using CRM systems to manage their customer relationships.

There are a number of challenges that businesses in Nepal face in implementing marketing technologies. These challenges include:

  • Cost: The cost of marketing technologies can be a barrier for many small businesses.
  • Lack of skilled personnel: There is a lack of skilled personnel in Nepal who can implement and manage marketing technologies.
  • Lack of awareness: Many businesses in Nepal are not aware of the different marketing technologies that are available and how they can be used to improve their marketing efforts.
  • Scattered data: Many small sellers take orders through Messenger, phone, and the shop counter, so their customer data is spread across chats and notebooks rather than one database.

Summary

Modern e-commerce marketing is powered by a stack of marketing technologies. Web transaction logs, cookies, pixels, and app data collect information about customer behaviour. Web analytics tools report traffic and conversions. Databases and data warehouses store customer data, and data mining finds patterns in it. CRM systems give a complete view of each customer, and marketing automation uses that data to send timely, personalized messages. Recommendation engines and programmatic advertising use the same data to choose products and ads in real time. These tools make marketing more efficient but raise privacy concerns, so consent and careful data handling are essential.

Key Takeaways

  • MarTech is the software and tools used by marketers, working together as a stack.
  • Logs, cookies, pixels, and device IDs collect behavioural data; first-party data is becoming more important.
  • Data warehouses combine data; data mining finds patterns (query-driven, model-driven, rule-based, collaborative filtering).
  • CRM gives a 360-degree view of the customer; marketing automation acts on it with triggered messages.
  • Programmatic advertising buys ads automatically through real-time auctions.

Discussion Questions

  1. How can a marketer use the data from Google Analytics to improve their website?
  2. What is the relationship between a CRM system and a marketing automation platform?
  3. Can a small business do digital marketing without using any MarTech tools?
  4. Where is the line between helpful personalization and invasion of privacy?

Exam-Style Questions

Short answer

  1. What is MarTech?
  2. Distinguish between first-party and third-party cookies.
  3. What is a data warehouse?
  4. What is collaborative filtering?
  5. Define programmatic advertising.

Long answer

  1. Explain the major online marketing technologies used by e-commerce firms to collect and analyse customer data.
  2. What is data mining? Describe its types with examples.
  3. Explain how CRM and marketing automation work together, using an abandoned-cart campaign as an example.