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How Incuda builds user journey models with Snowplow

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Presented at Snowplow Berlin Meetup, November 2016

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How Incuda builds user journey models with Snowplow

  1. 1. © incuda GmbH incuda BI for multi-channel commerce data-drive your business.
  2. 2. incuda BI for multi-channel merchants data-drive your business: One better Decision every day © incuda GmbH . 2 we track behaviour, interest & profitability of >200 mln. persons from over 100 countries … … on a daily basis Founded 2012, Munich & Düsseldorf. Partners for strategy, business consulting, technology & implementation. Market focus: E-commerce & multi-channel merchants, international & multi-brand, yearly revenue 20+ mln. €. Mission: Provide a more mature & powerful BI platform in time of increasing competition.
  3. 3. Agenda data-drive your business: One better Decision every day © incuda GmbH . 3 describe an advanced user journey model see how a journey-based view helps to optimize - Marketing Performance - Relationship Marketing - Product Performance understand why Snowplow plays a critical role to achieve overall success. discuss your ideas and questions, ask anytime
  4. 4. Background
  5. 5. Measuring Success: User Journeys data-drive your business: One better Decision every day © incuda GmbH . 5 User Journeys are an excelent tool to measure impact of offers and ad items in a highly parallel marketing environment. We focus on Journeys which include digital channels, Snowplow is our tool for collecting information and allows us to build high-quality journeys on a granular level. approach description devices channels Keywords, banners View/click ad item, Last Click conversion single single Campaigns Response across time and channels single multiple Journeys Contacts over time and conversion for next order multiple multiple Cohorts mid-/long-term customer lifetime & value multiple multiple
  6. 6. Why is Journey modelling difficult? data-drive your business: One better Decision every day © incuda GmbH . 6 Good customers on average use − 5 marketing channels, 4 contact devices, − 1.2 customer IDs, − 1.3 email addresses. Over 80% of repeat buyers use more than 1 contact device. More than 80% of marketing cost & journeys are on non-buyers.Number of devices per repeat buyer within 12 months. Impact on: - Marketing Performance: different devices used during information / conversion phase - 360° user view on buyers and non-buyers - Buying & interest behaviour for different product categories, brands, price ranges
  7. 7. What happens if you are working with raw data? data-drive your business: One better Decision every day © incuda GmbH . 7 Raw data experience: - you see many very short buyer journeys - mobile journeys with clear product interest but no conversion - buyers visit at other time of day than non-buyers Our learnings: − most products are viewed before ordered, but often not on the same device. − People use different devices for information phase (mobile, work, second-screen) and for orders (desktop, home). − People use different devices during the day − Family & friends use the same desktop device (cookie ID) − cross-device detection happens over time, requires„automatic“ updates of the user journey (ongoing & historical data)
  8. 8. Process & Application layers provide interaction data data-drive your business: One better Decision every day © incuda GmbH . 8 Campaigns & Offers Touchpoints Customer transaction Order intake Revenue Cancel & Returns Cogs, Pick & Pack Raw margin, PC-I Marketing cost, Commissions, .. PC-II Werbemittel-Detailebene Buyer & Nonbuyer contacts Transactions & Customers ad media ID ad media ID transact ID transact ID … Profit-driven performance marketing Conversion; Cost per Offer / Ad item Traffic acquisition Cost of traffic, Conversion, Repeat traffic, … - Sequence of channels - Conversion rates - User Lifecycle CRM outbound marketing many few one
  9. 9. Layers are woven into a „Data Network“: more = higher density data-drive your business: One better Decision every day © incuda GmbH . 9 Desktop PC (Cookie) Mobile Workplace PC visit visit visit visit visit Email Call Center Online-Shop Customer ID Order ID, Product data Catalog, Ad-ID, Offline Advertising Contact data (email, phone) Order, Case ID Email click Email click Channels Touchpoints Customer transaction Tracking tools Channel backend data Data Warehouse / ERP Subscribe Log-in Order Campaign Email open Subscribers call
  10. 10. Case Study: Journey length, based on User Consolidation Case: established international Online Retailer, comparison based on German shop − Scenario A: modelling by established Journey agency, based on online data − Scenario B: enhanced modelling based on online & inhouse data (incuda) data-drive your business: One better Decision every day © incuda GmbH . 10 Quantitative findings: − 50% of Buyer Journeys in scenario A with only 1 or 2 contacts (compared to 32% Journeys B) − Scenario B shows over 2 times more Journeys with 7+ contacts Qualitative findings (based on analysis of examples): Journeys show a more consistent approach to conversion (product information before orders) Number of user interactions more in-line with experience of business experts Validated responses from outbound communictaion confirmed device usage
  11. 11. Case Study (cont.) Impact: More complete description of decision funnels, better understanding of channel interaction „longer“ journeys provide more opportunities for conversion impulses More correct allocation of marketing cost to conversion Why worked approach B better? - integration of multiple devices in one journey - integration of more touchpoints (offline, offsite) - access to inhouse data - configuration of technical processes to provide required data - full utilisation of webtracking platform (tracking, parameterisation, cookie types) data-drive your business: One better Decision every day © incuda GmbH . 11
  12. 12. Our Learnings data-drive your business: One better Decision every day © incuda GmbH . 12 Integrated Journey modelling impacts: - Marketing Performance: different devices used during information / conversion phase - 360° view on buyers & non-buyers, Lifetime estimates and opportunities for CRM activities - Buying behaviour for different product categories, brands, price ranges Tracking of contact history should include as many touchpoints as possible. Owned & offline channels (email, print, co- operations, etc.) improve metrics for ongoing user activity. Tracking platform must have all the flexibility which you will need in the future ; blackbox approach might be risky. We like Snowplow with the Open Source approach, transparent source code and architectural flexibility.
  13. 13. How do we do it?
  14. 14. User – Device detection & consolidation Users can be merged at any time; automated integration of contact history and user profile data is required for a performant platform management. Level 1 Secure matching - Matches devices, accounts and contact addresses through events and data that clearly identify a user - Examples: Orders, Email address, log-in to user account Level 2 High-probability matching - Matches devices, accounts, contact data, and other information through events and data that identify the user of the device with a high probability - Mapping is reversible in case problems are detected - Examples: Email click-through, contact information and identifiers Level 3 Post-technical validation - Confirm or reject matches, based on functional rules (abstraction from technical level) - Complete control to analyse & overrride single consolidations, DQ checks - Examples: Manage household users, friends sessions, etc. data-drive your business: One better Decision every day © incuda GmbH . 14
  15. 15. campaign contact campaign contact0 User consolidation: examples for consolidation rules User Master User User Response (e.g. Snowplow online visit) new user devices known user devices campaign contacts user contact data log-in to user account subscribe to service / email referrer = email click-through order (incl. guest orders) customer service request − initial = 1:1 − Data Load consolidation = 1:N user account Level 1 consolidation „secure match“Level 2 consolidation „high probability“ − initial = 1:1 − Logical matching rules − Batch consolidation on earliest user ID Post-technical validation Post-technical validation Functional validation Level 3 consolidation „post-technical validation“ data-drive your business: One better Decision every day © incuda GmbH . 15
  16. 16. Our Learnings data-drive your business: One better Decision every day © incuda GmbH . 16 User consolidation needs to be 95% precise, otherwise you cannot use it for personalisation / targeting and you loose a big part of the business value. Transparency on single cases and option to change every consolidation is critical! Use tagging & cookie features to track across (sub-) domains and brands. Use custom fields for additional IDs. At the same time, make sure that you retain a precise view on transactions (shipping address, email address per order, etc.). Otherwise you will run into limitations for transaction mails.
  17. 17. How we build dynamic Attribution curves data-drive your business: One better Decision every day © incuda GmbH . 17 When you have the base data in place, calculation of journeys is straight forward: - consolidate contact history & group by conversion events - update journeys every time a user consolidation gets updated - Calculate per contact & single admedia item (detail level) - Take care of system performance From the feature list: − user defined curves; bath-tub, dynamic u-curve; channel boost factors (DTI, TV, …) − age of contact relative to journey end − duration between contacts in journey − onsite engagement − early timeout predictor for ongoing business − compare different models, champion challenger approach
  18. 18. Understanding Journey pattern The structure of Journeys first gives you an insight into the usage of you contact channels and ad items. The sequence of channels used helps to understand typical acquisition and conversion scenarios for new users, active customers, top buyers, etc.: - Sequence of marketing channels - Sequence of device types (mobile, desktop,…) - Sequence of daytime hours for information and conversion On top, the main impact of an offer or ad item during the AIDA decision funnel is measured: some offers have a low conversion, but a high acquisition or re-activation value. data-drive your business: One better Decision every day © incuda GmbH . 18
  19. 19. Our Learnings data-drive your business: One better Decision every day © incuda GmbH . 19 Journey structure on user base gives you a first segmentation of users who behave in a mono-like way (strong preference for contact channel, device, daytime hour) and other users with more flexible behavior. Journey structure shows, if information phase and conversion happen on the same timeline: which users buy directly, which have a time-related pattern (e.g. buy in the evening from home, order on weekend) AIDA modelling gives you additional metrics (activation, reactivation) for performance tuning.
  20. 20. Integrated Marketing Calendar data-drive your business: One better Decision every day © incuda GmbH . 20 A broader integration of touchpoints leads to better journey data: include all marketing & sales activities and relate them to user contacts. − Add campaign metadata (clear names) and cost figures. − Break ad cost down to single contacts. − Add a meta layer to connect between cost reports and click-data tagging. A standardised description of marketing activities & cost is the basis for - flexible and automated calculation of user journeys - dynamic attribution modelling.
  21. 21. Marketing performance: manage on ad-item level & profitability Measure financial success for single ad items. Define success metrics according to your business model, e.g. net revenue or profit contribution instead of KUR. Automate baseline business and push financial metrics to tools for Autobidding, campaigns, email, sourcing, ... Compare metrics between time periods and understand changes on different levels (traffic, advertising, visitor structure, product quality, return rates) and their impact on marketing performance. data-drive your business: One better Decision every day © incuda GmbH . 21
  22. 22. Customer understanding: User Profiling & Segmentation Profile user segments based on all data available: - navigation on the shops - marketing channel and device usage - product & category interest - buying patterns, including revenue, returns, profitability - geography, gender, age, statistical data on households, income, education, etc. Customer Understanding is based on what users buy, what they are interested in, and what they are not interested in… Detailed click data enables data feeds to support CRM, Lifecycle alerts and Outbound Segment marketing. data-drive your business: One better Decision every day © incuda GmbH . 22
  23. 23. Our Learnings data-drive your business: One better Decision every day © incuda GmbH . 23 Design advertising channels in a consistent way: - inbound vs. outbound marketing - direct vs. indirect channels (TV) - cost models (CPM, CPC, CPO, CPL) Link marketing cost to single contacts, not orders. Key measure is the cost for a given contact. Snowplow tracks campaing information on ad-item level; do not track on aggregated campaigns! Use CPM, CPC, KUR? Optimise according to your business model! e.g. net revenue, profit, or your custom metrics. Make sure your tracking tool supports flexible mapping of click data information to marketing cost reports. Understand your users based on what they do (buy, view) and what they don‘t do. (requires a complete user view!)
  24. 24. Products meet Sales: the “Product Journey” data-drive your business: One better Decision every day © incuda GmbH . 24 Different types of products can have different roles: from building your brand to attracting visitors and finally converting into revenue, not all products behave in the same way. But at the end of the day, product stock should be sold out or at leas minimised. And higher demand should be identified as early as possible. The „product journey“ identifies interest levels, leads and prospect buyers for individual articles: - for onsite, offsite, aftersales channels - for buyers and non-buyers - for converted and dropped articles - based on net revenue & profit contribution
  25. 25. Tracking product interest data-drive your business: One better Decision every day © incuda GmbH . 25 Product orders are available from backend systems. The major data source for Product interest data is the tracking tool. We use Snowplow tracking to gather event detail data - Product views - Basket add or remove events - Basket convert - Product impressions on home page, overview pages - Product detail information from filter, search, etc. events on detail level (large amount of tracking data!) - other events, like registrations, service requests, … The flexibility and scalability of snowplow allows us to get all interaction data we require and add it to the users contact history. The contact history allows us, to measure effects over time, e.g. out-of-stock & purchase probability.
  26. 26. Matching click events to marketing effort and conversion data-drive your business: One better Decision every day © incuda GmbH . 26 Product profitability is usually measured on converted orders. Brands and categories attracting traffic but with lower conversion are undervalued with this “last click” logic (same last click in online marketing ). The “product journey” maps product- or service-related events into the onsite journey and attributes marketing cost and journey revenue to each event. This gives a more balanced view on the contribution of products and brands to conversion (category and brand management). Weighting of product views within visits (same color). All events of a visit (same colour in chart) are weighted according to the attribution curve (acquisition-based u-curve). Event types (view, add, buy) are weighted according to their stage in the conversion funnel.
  27. 27. Products meet Sales: the User- and the Product Journey data-drive your business: One better Decision every day © incuda GmbH . 27 The Product Journey shows you the attributed value each product on your sales channels contribute to final sales. Not only Products with good “last-click” behavior are rated highly, but also - Products, categories and brands which acquire new customers - Products, categories and brands which generate repeat visitors, e.g. from Email - Lost opportunities per product and category, linked to user profiles Marketing campaigns lead the users to your sales channels, use the product journey to optimize your onsite conversion.
  28. 28. Agenda data-drive your business: One better Decision every day © incuda GmbH . 3 describe an advanced user journey model see how a journey-based view helps to optimize - Marketing Performance - Relationship Marketing - Product Performance understand why Snowplow plays a critical role to achieve overall success. discuss your ideas and questions, ask anytime
  29. 29. Agenda data-drive your business: One better Decision every day © incuda GmbH . 3 describe an advanced user journey model see how a journey-based view helps to optimize - Marketing Performance - Relationship Marketing - Product Performance understand why Snowplow plays a critical role to achieve overall success. discuss your ideas and questions, ask anytime

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