Integration enhances ad performance by leveraging LTV data, allowing advertisers to optimize ad spend for maximum profitability and efficiency across channels

Shirofune, the leading digital advertising automation management platform, announced its integration with BigCommerce, a leading open SaaS ecommerce platform for fast-growing and established brands, to predict and optimize ad campaigns based on Customer Lifetime Value (LTV). This integration highlights Shirofune’s continued expansion into the ecommerce space and provides advertisers with a new level of sophistication in ad performance optimization, delivering better decision-making insights to maximize long-term profitability.

“We are thrilled to unveil Shirofune’s new BigCommerce integration, bringing even greater value to advertisers by helping them optimize campaigns based on customer lifetime value,” said Shirofune Founder and CEO Mitsunaga Kikuchi. “In today’s fast-evolving digital landscape, long-term profitability is more crucial than ever. By integrating with BigCommerce, we are empowering advertisers to not just optimize for short-term gains but to see the full picture and allocate ad spend more effectively. Advertisers who leverage LTV data will gain a competitive advantage in driving sustainable growth and maximizing ROI for their clients.”

Shirofune’s integration with BigCommerce allows advertisers to connect ad performance data with customer lifecycle insights, including whether customers are new or returning, their purchasing behaviors, and predicted LTV. By analyzing this data, Shirofune automatically allocates ad budgets towards campaigns and channels that are most likely to drive higher lifetime returns on ad spend (ROAS), rather than focusing solely on immediate conversions.

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Recent fully automated campaigns on major ad platforms tend to focus more on keywords and audiences that include a higher percentage of existing customers, which are easier to drive short-term sales. By properly visualizing metrics such as LTV and allocating budgets based on the long-term performance of each campaign, advertisers and agencies can ultimately improve the overall ROI of their advertising efforts.

Other benefits that marketers can experience through this integration include:

• Data-Driven Decision Making: Leverage BigCommerce data to track customer behavior, identify whether customers are new or returning, and allocate ad spend towards campaigns that yield the highest lifetime returns on ad spend (ROAS).
• Omnichannel Ad Management: Optimize ad performance across all major platforms including Google, Microsoft, Meta, TikTok, and X (formerly Twitter) using Shirofune’s advanced AI-driven algorithms.
• Automated Campaign Management: Automate complex tasks such as budgeting, bidding, and performance analysis, saving advertisers significant time while improving efficiency and performance.
• Seamless Integration: Connect ad performance data with BigCommerce customer data to streamline campaign management, allowing advertisers to make better, faster decisions without manual data synchronization.
• Improved ROI and Productivity: By focusing on lifetime value and automating daily tasks, Shirofune enables advertisers to boost ROI, reduce manual work hours, and drive long-term business growth.

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Shirofune’s integration with BigCommerce enhances its already robust omnichannel ad management capabilities, covering platforms such as Google, Microsoft, Meta, TikTok, and X (formerly Twitter). The platform’s advanced AI-driven algorithms streamline ad management by automating complex tasks such as budgeting, bidding, and performance analysis.

“The Shirofune platform was designed to automate the labor-intensive aspects of ad management, freeing advertisers to focus on strategy and long-term growth,” Kikuchi added. “With this new integration, advertisers can now harness the full potential of BigCommerce data to drive better results across every digital touchpoint.”

Other recent product announcements include the enhancement of its Shopify integration with Google Analytics 4’s data-driven attribution model and the incorporation of its Improvement Suggestion feature for Amazon Ads and Microsoft Ads.