Sellpoints moves beyond last-click attribution to double performance of non-brand paid search and triple performance of display
Customer Company Size
SME
Region
- America
Country
- United States
Product
- Google Analytics
- AdWords
Tech Stack
- Multi-Channel Funnels
- Position-based model
- Time-decay model
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Revenue Growth
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Retail
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Quality Analytics
- Demand Planning & Forecasting
Services
- Data Science Services
About The Customer
Sellpoints is an expert in online selling, founded in 2000 and based in Emeryville, CA. The company aims to help its global clients make informed marketing decisions and drive performance improvements. They wanted to obtain a more accurate understanding of users’ paths to conversion. The agency understood that those advertisers who give all the credit for a sale only to the final click along the conversion path aren’t getting a true reflection of reality. They realized the need for a more comprehensive analysis that takes into account the entire conversion path, from the initial search to the final click.
The Challenge
Sellpoints, an expert in online selling, wanted to help one of its global clients make informed marketing decisions and drive performance improvements. The agency aimed to obtain a more accurate understanding of users’ paths to conversion. They realized that attributing all the credit for a sale to the final click along the conversion path doesn't provide a true reflection of reality. Conversion paths are complicated; a user may begin with a search using generic terms, see and click on a display ad, perform another search later using narrower branded keywords, click on a paid search ad and eventually convert after a wide variety of online actions. A last-click analysis ignores all of these actions except the final one.
The Solution
Sellpoints used Google's range of tools to move beyond the last click. The agency used Multi-Channel Funnels, a feature of Google Analytics, which can also incorporate Display impressions, to show how users convert across a range of online channels. It also applied insights into customer behavior to create models tailored specifically to its client, using a combination of a position-based model and a time-decay model. In valuing each step along the conversion path, Sellpoints’ analysis turned up a number of important discoveries. It determined that in a last-click model, 30% of conversions were attributed to brand keywords. Using its combination of position-based and time-decay models, Sellpoints was able to demonstrate that 40% of these in fact had started on a non-brand interaction.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Case Study
Digital Retail Security Solutions
Sennco wanted to help its retail customers increase sales and profits by developing an innovative alarm system as opposed to conventional connected alarms that are permanently tethered to display products. These traditional security systems were cumbersome and intrusive to the customer shopping experience. Additionally, they provided no useful data or analytics.
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Case Study
Ensures Cold Milk in Your Supermarket
As of 2014, AK-Centralen has over 1,500 Danish supermarkets equipped, and utilizes 16 operators, and is open 24 hours a day, 365 days a year. AK-Centralen needed the ability to monitor the cooling alarms from around the country, 24 hours a day, 365 days a year. Each and every time the door to a milk cooler or a freezer does not close properly, an alarm goes off on a computer screen in a control building in southwestern Odense. This type of alarm will go off approximately 140,000 times per year, equating to roughly 400 alarms in a 24-hour period. Should an alarm go off, then there is only a limited amount of time to act before dairy products or frozen pizza must be disposed of, and this type of waste can quickly start to cost a supermarket a great deal of money.
Case Study
Supermarket Energy Savings
The client had previously deployed a one-meter-per-store monitoring program. Given the manner in which energy consumption changes with external temperature, hour of the day, day of week and month of year, a single meter solution lacked the ability to detect the difference between a true problem and a changing store environment. Most importantly, a single meter solution could never identify root cause of energy consumption changes. This approach never reduced the number of truck-rolls or man-hours required to find and resolve issues.