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Key Performance Indicators and Measurement Framework
A Measurement Framework is a way to observe and make sense of data. It brings marketing decisions back to reliable and actionable indications. The framework serves three primary purposes in the context of MMM:
- It establishes specific objectives that link marketing efforts with sales results.
- It sets common measures to be applied across channels and campaigns.
- It makes for a feedback loop, enabling constant refinement from performance data.
Ecommerce KPIs necessary for MMM Analysis
Sustainable MMM requires understanding both the totality of impact and marginal profit. The means by which you can analyze all these aspects of ecommerce are summed up in the Web KPIs below.
Revenue Metrics
- Sales excluding VAT post returns – Reflect sales after discounts and exchanges are applied, providing a close approximation of what customers will have paid.
- After subtracting VAT – Amount after returns by VAT included, provides a better picture of sustainable extracts related to marketing revenue in connexion.
- Gross Margin post-returns – Measures profitability after returns are factored into the equation by taking COGS away from net sales, illustrating true financial impact.
Customer Acquisition Metrics
- Customer Acquisition Cost (CAC) – The total dollars spent on marketing and sales divided by the number of new customers, which can reveal channel efficiency.
- Customer Lifetime Value (CLV) – The predicted revenue a customer generates over the entire relationship essential for your long-term ROI analysis of acquisition.
- CAC to CLV Ratio – The ratio of how much it costs to acquire a customer vs. the projected lifetime earnings; if less than one this is good unit economics.
Channel Performance Metrics
- Return on Ad Spend (ROAS) – The amount of revenue generated in relation to the money spent on an advertisement or campaign, and is calculated by subtracting your ad spend from your revenue.
- Advertising Cost of Sales (ACOS) – How much you spend on ads vs. how much you earn from ads, the lower your ACOS the more effective your advertising.
- CPA (Cost Per Acquisition) – The cost for acquiring one customer through a given channel, useful for setting budgets across platforms.
Advanced Attribution Modeling
Credit for each sale is distributed to different touchpoints based on an attribution model. Current-state MMM employs sophisticated techniques to more accurately account for customer journeys:
Multi-Touch Attribution Models
- Linear Attribution – All touchpoints receive equal weight, so that all interactions from Awareness through to Conversion are shown.
- Time-Decay Attribution – Attributes more influence to touchpoints nearer the conversion, bringing focus to recent actions that are most likely responsible for driving a sale.
- Position-Based (U-Shape) Attribution – It will give the most credit to #1 and #3 Touchpoints acknowledging both the discovery of the an initial interaction and final action before covering multiple touch point interactions in between.
- Data-Driven Attribution – This utilizes machine learning to analyze historical conversion paths and gives credit based on assumed statistical significance as opposed to fixed rules.
How trivas.ai Elevates Your MMM Analytics
trivas.ai's holistic AI platform that streamlines every aspect of your MMM process:
- Automated data ingestion: Seamlessly connects to your ecommerce and ad platforms consolidating revenue, cost, and customer data on a single dashboard.
- AI-Powered Modeling: Leverages advanced AI algorithms to generate personalized MMM models (such as MTA and channel interactions) without manual coding.
- Real-Time Intelligence: Only tool that offers KPI tracking at an enterprise level for same day budget and strategy adjustments.
- Infographics & Reports at Scale: Automatically produce ready for exec reports and infographics – such as conversion funnel diagrams and ROI comparisons, to ensure stakeholders are informed.
- SEO-Optimized Reporting: Delivers thorough insights and documentation perfect for search engines, so you can increase your visibility and rankings to drive more organic traffic.
By utilizing trivas.ai, marketing teams can convert their MMM analysis from static spreadsheet models to actionable predictive models that will power better decisions, scaling spend efficiently and delivering growth.
