DMA 7040 Module 1 Five Questions Assignment: The Digital Value Chain Example

From Search to Sewing Room: Five Questions on the Digital Value Chain of a Vintage Machine Seller

Student Name

MBA in Marketing, Thomas Edison State University

DMA-7040: Digital Marketing Analytics

Mentor Name

Month Day, Year

From Search to Sewing Room: Five Questions on the Digital Value Chain of a Vintage Machine Seller

Question 1: What is the digital value chain, and where does analytics add value in it?

The digital value chain is the series of activities through which a firm creates value for customers online: attracting attention, engaging visitors, converting them into buyers, fulfilling and supporting the purchase and bringing customers back. For Riverbend, the chain starts when a quilter searches for a 1950s Singer Featherweight or a replacement bobbin case, continues through product pages, photos and a "will it sew denim?" guide, reaches checkout or a phone call and ends with a shipped machine, a tune-up reminder a year later and, ideally, a review.

Analytics adds value at each link by replacing opinion with evidence. At the attraction stage it shows which searches and referring sites bring visitors who buy, not only visitors. At the engagement stage it shows which pages hold attention and which lose it. At conversion it shows where checkout fails. After the sale, it connects repeat purchases and reviews to the first visit. Wedel and Kannan (2016) argue that the value of marketing analytics lies in linking these stages, because a measure at one link, such as clicks, can rise while the outcome at a later one, such as profit, falls.

Question 2: How does Kaushik's Web Analytics 2.0 model apply to Riverbend?

Kaushik (2009) argues that clickstream data alone describe what visitors did but not why, or what it was worth. His model combines five sources, with insight as the goal at the center:

Riverbend today uses only the first source and a little of the second. Its owner knows the site had 52,000 visits last quarter but not which visitors later phoned in an order, why half of visitors to the Featherweight page leave within a minute or whether rivals have cut prices. Adding outcomes and voice of customer would be the cheapest gains, since both data sets already exist in the order system and the call log.

Question 3: What are Riverbend's macro and micro conversions?

Kaushik distinguishes the main purpose of a site, the macro conversion, from smaller actions that signal progress or value of their own, the micro conversions. Riverbend's macro conversions are a completed online order and a booked repair. Its micro conversions include adding a machine to a wish list, downloading a free manual, signing up for the restock email, watching a threading video and clicking the phone number on a mobile device. Each micro conversion has a different meaning. A manual download often comes from someone who already owns a machine and may need parts or service later, while a phone-number click from a product page often precedes a phone order that the website never sees. Tracking both kinds lets the firm credit pages and campaigns that start relationships rather than only those that close sales.

Question 4: How can traditional, multichannel and digital data be integrated?

About a third of Riverbend's revenue never passes through its website checkout: buyers of expensive machines often phone to ask about a specific model before paying, repair customers walk in, and marketplace buyers check out on the marketplace. Three steps would join these channels to the web data. First, every phone order should be logged with a source question ("Where did you first see the machine?") and, where possible, the product page the caller mentions; a dedicated phone number on the website, different from the one on marketplace listings, separates web-driven calls from others. Second, repair tickets and marketplace orders should be matched to the customer list by email address so a customer's full history sits in one record. Third, the firm should compare monthly totals across channels rather than judging each channel alone, because a marketplace listing may lead buyers to search for the Riverbend name and buy direct. Lemon and Verhoef (2016) describe the customer journey as crossing many touchpoints the firm does not control, which is why integrated data matter more than any single channel's report.

Question 5: Which tools should Riverbend start with?

A small seller should begin with free or low-cost tools and a clear measurement plan rather than an expensive platform. Riverbend's starting set would be Google Analytics 4 for clickstream and conversion events, Google Search Console for the searches that bring visitors, the order and repair systems it already uses for outcomes, a two-question post-purchase survey for voice of customer and a spreadsheet dashboard that combines web, phone, repair and marketplace sales each month. A testing tool can come later, once the site has enough traffic for tests to reach clear results. The strategy matters more than the tools: decide the business questions first, define the conversions that answer them and only then configure the software, as Kaushik advises.

References

Kaushik, A. (2009). Web analytics 2.0: The art of online accountability and science of customer centricity. Wiley.

Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96. https://doi.org/10.1509/jm.15.0420

Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97-121. https://doi.org/10.1509/jm.15.0413