Customer journeys are more complex than ever. They span many devices, touchpoints, and channels, and individuals move through them, and their customer lifecycle stages, quickly.
Despite this complexity and speed, customers expect companies to deliver value along their entire customer journeys (and respect their individual privacy preferences in the process).
The only way consumer goods companies — retailers, CPG businesses, etc. — can deliver the ideal messaging and experiences to their customers at the optimal moments in their journeys is by wholly understanding those journeys in real time.
That means they need technology in which they can unify customers’ demographic, engagement, interest, and behavioral data as well as online and offline transactional data.
Transactional data’s role in consumer companies’ omni-channel strategies
The cookie’s crumble continues to impact consumer companies‘ engagement strategies.
A 2021 IAB and Ispos survey found the top way businesses are adjusting to post-cookie life is by prioritizing first-party data collection and utilization. Demographic, device, and location data are the core first-party data points they collect.
But less than half (42%) of these companies collect transactional data, according to the report. This is a missed opportunity, as the lack of real-time online and offline purchase data means these businesses lack a true single customer view.
They may know individuals’ product interests, website frequency, and other important attributes. But historical transactional data for every customer in their tech ecosystem is vital to their segmentation, modeling, analysis, and activation success.
Gathering and leveraging this data is also what consumers now expect from businesses:
- 83% of consumers said they want their shopping experiences personalized across channels by companies based on past purchases. — 2020 McKinsey research
- 72% of consumers expect businesses from which they buy to “know their purchase history regardless of the method of communication.” — Nice inContact report
- 74% of consumers want product recommendations based on their purchases, while 54% like email and ad reminders for abandoned-cart items. — 2021 Econsultancy survey
The pros of using purchase data to deliver one-to-one, omni-channel experiences are many.
For instance, a 2019 BCG and Google study discovered consumers are 110% more likely to add items to their shopping carts and 40% more likely to spend more than initially intended when their buying experiences are personalized across channels and based on bought products and expressed interests.
“You can use transaction data to identify who might be a probably buyer of a new product, incent the customer by providing a targeted offer, and determine how your program worked,” consultant Claude Johnson wrote for Chief Marketer.
Consumer companies can’t use just any database to leverage transactional data, though.
They need a single source of truth in which they can unify first-party data — including purchase data — that’s accessible to marketing, CX, analytics, and other growth-focused teams when and where they need it to drive engagement and deliver optimal experiences.
As the IAB and Ipsos survey discovered, that’s what many businesses are adopting today.
The report found 62% of consumer companies are investing in solutions like customer data platforms (CDP) to improve their customer identity resolution and first-party data utilization.
How consumer companies use BlueConic to make the most of transactional data
Many consumer companies enhance their identity resolution and make the most of their first-party customer data in their omni-channel strategies with BlueConic.
They unify data from across their technology stacks — including transactional data from MDM, CRM, POS, and other systems — into BlueConic’s persistent customer profiles, in which unique event timelines are created for each customer.
Views, clicks, and orders are three key out-of-the-box (OOTB) profile timeline events BlueConic collects from these tools. Our CDP also allows companies to create custom event types (e.g., customer service interactions, form submissions), which can be based on other event data stored in these systems.
For instance, retailers can connect their ecommerce and/or POS solutions to BlueConic. This enables them to merge online and offline order data into individuals’ profiles and use it for multi-dimensional segmentation and predictive modeling.
Companies can also use our SFTP connection to upload CSV files featuring other online and offline transactional data sets (e.g., total orders, specific products and/or product categories purchased, date and location of in-store purchases) into BlueConic.
This helps them further enrich customer profiles and ensures their growth-focused teams have access to only the highest-quality, most relevant, up-to-date customer data.
With unified behavioral, engagement, and transactional data, BlueConic customers can:
- Deploy OOTB customer lifetime value (CLV) and recency, frequency, and monetary value (RFM) models to calculate customer scores and predict revenue for individuals over time
- Import custom notebooks into AI Workbench to further understand customer behavior
- Create time-based segments based on profile data that originated in the timeline
- Use purchase data to improve cross-channel product recommendations (e.g., on-site dialogues, targeted ads, open-time email recommendations)
- Export transactional data to other systems for further activation and/or analysis
Our OOTB CLV and RFM models in AI Workbench, in particular, are especially beneficial.
One retailer merged online and offline purchase data with behavioral data in BlueConic to calculate CLV and RFM scores at the individual level. This helped it create new segments like ‘Champions,’ ‘Potential Loyalists,’ and ‘Needs Attention’ and target them and lookalike audiences on Google and Facebook.
In-store associates also use the segments to identify high-priority shoppers. They provide VIP treatment to individuals in these segments when conducting outreach over the phone and when customers visit brick-and-mortar locations.
Accelerating your omni-channel strategy with purchase data and a pure-play CDP
Unifying transactional data — as well as other minimum viable data needed to execute core use cases — in a CDP is just step one for consumer companies following implementation.
“To maximize first-party data as a strategic and competitive asset, it must also be accessible to the functions within the company that are responsible for driving growth, such as marketing, ecommerce, and analytics,” BlueConic VP Marketing Michele Szabocsik recently wrote for Total Retail.
To break that down further, access to historical transactional data enables these teams to:
- Compare and contrast customer segments to learn where (i.e., specific channels, online vs. offline) and when (e.g., time of day, immediacy following email click-through) they buy and what factors (e.g., individualized homepage experience) influence purchases
- Deploy OOTB and/or custom predictive models to determine customers’ CLV and RFM scores as featured in the example above and their propensity to buy and churn over time based on their recent behavioral, engagement, and purchase data
- Orchestrate intelligent lifecycle messaging that benefits both the customer (e.g., offers for products related to ones previously bought, suppressed promotional messaging to high-frequency shoppers) and business (e.g., greater customer loyalty and revenue)
Accelerating your omni-channel strategy and improving the performance of key programs (seasonal promotions, holiday campaigns, etc.) are likely primary goals for your company.
And leveraging first-party data — including dynamically updated transactional data for opted-in customers — in a CDP is your best bet for realizing your desired ROI.
Download our omni-channel acceleration eBrief today to discover how retailers, CPGs, and other consumer companies realize better marketing and business outcomes with a CDP.