Experts at Calltouch explain why it is important to track the entire user journey from the first touchpoint to social media feedback, what hidden losses can lead to critical problems, and how to establish high-quality data collection.
On the market, it is not uncommon for businesses to experience stagnant or even declining overall profitability despite substantial marketing budgets and perceived conversion growth. One of the most common reasons for this situation is the presence of “blind spots” in promotion and sales. Typically, these arise from inaccurate or fragmented data used when testing hypotheses and making decisions.
Here are the most frequent “blind spots” in analytics that business people encounter:
- Ineffective advertising campaigns. There are many reasons why a launched campaign fails to deliver the desired results: poorly chosen platforms, incorrectly calculated targeting, visuals that do not resonate with the audience or fail to overcome “banner blindness.” End-to-end analytics allows you to examine each of these aspects and adjust your inputs.
- Weak links in the sales funnel. Even the most well-planned strategy can be undermined by what seems like a minor detail. Inconvenient website navigation, a poorly designed shopping cart, lack of information about advertised promotions on the home page, and so on. With end-to-end analytics, you can identify where the customer breaks contact with the product and eliminate the vulnerability.
- Incomplete conversion attribution. Misjudging the effectiveness of different communication channels can lead to investing in the least profitable ones. A user might discover a product through a radio ad, visit the website via a search engine, but make the purchase on a marketplace. There are also so-called “invisible channels” that boost brand recognition and loyalty (such as video hosting platforms or native integrations in articles), though customers do not arrive directly through them. End-to-end analytics helps track such scenarios and continue investing in channels that serve as a communication foundation, even if they do not drive direct traffic.
- Low-quality traffic. Conversions can suffer from non-targeted leads: bots, artificially inflated clicks, accidental clicks, and irrelevant calls. End-to-end analytics also helps identify the share of such leads and set up appropriate filters.
- Unprofitable products and promotions. With end-to-end analytics, you can identify items in your assortment with low margins and high promotion costs. A prime example is selling a product as part of a promotion where customer acquisition costs (CAC) are too high, guaranteeing a loss on every transaction.
Data quality control tools
- Automated quality control. Automation is essential for effective data quality management. Key tools include data profiling (automated analysis of data structure, distribution, and characteristics), validation (ensuring data meets defined rules and requirements), change monitoring, and automated alerts that trigger when critical metrics deviate from expected thresholds.
- Standards and best practices. For example, the DAMA-DMBOK provides comprehensive guidance for data management, while the ISO 8000 standard addresses data quality and interoperability challenges in data exchange between systems.
- Regular audits. Ongoing verification and evaluation of data are required to assess its accuracy, quality, and continued relevance.
End-to-end analytics built on high-quality data turns scattered figures into a coherent strategic roadmap, revealing hidden losses and enabling targeted improvements at every stage of the customer journey.