Sales Funnel Analytics

This guide covers the Wildberries Sales Funnel API (v3) and explains how to use the SDK to retrieve, filter, and analyze product performance data at every stage of the buyer journey.

Target Audience: Developers building analytics dashboards, product managers tracking conversion metrics, and data analysts working with Wildberries seller data

Prerequisites: SDK installed and configured, valid API key with Analytics permissions

Estimated Reading Time: 25 minutes

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Table of Contents

1. What is the Sales Funnel
2. SDK Methods
3. Key Metrics Reference
4. Filtering and Sorting
5. Practical Scenarios
6. CSV Reports for Extended Periods
7. Rate Limits
8. Error Handling
9. Related Resources

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What is the Sales Funnel

The sales funnel on Wildberries tracks the buyer journey from initial product discovery through to a completed purchase that the customer keeps. The Wildberries API provides quantitative metrics for each stage, allowing you to measure how effectively your products convert browsing activity into revenue.

Funnel Stages

Impressions (openCount)
    Product card views -- the customer opens the product page
        |
        |  addToCartPercent  (view-to-cart conversion)
        v
Cart (cartCount)
    Customer adds the product to their cart
        |
        |  cartToOrderPercent  (cart-to-order conversion)
        v
Orders (orderCount / orderSum)
    Customer places the order and pays
        |
        |  buyoutPercent  (order-to-buyout conversion)
        v
Purchases (buyoutCount / buyoutSum)
    Customer receives and keeps the product

At each transition, a percentage of customers drops off. The SDK returns conversion rates for every transition so you can identify where products lose the most potential buyers.

Cancellations (cancelCount, cancelSum) are tracked separately and represent orders that were placed but later cancelled before or after delivery.

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SDK Methods

The Analytics module provides three methods for sales funnel data. Each targets a different analytical use case.

getSalesFunnelProducts -- Summary Report

Returns a paginated list of products with aggregated funnel metrics for a selected period. Optionally compares the selected period against a past period, producing delta values for every metric.

Period limit: up to 365 days.

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

const report = await sdk.analytics.getSalesFunnelProducts({
  selectedPeriod: {
    start: '2026-01-01',
    end: '2026-01-31',
  },
  pastPeriod: {
    start: '2025-12-01',
    end: '2025-12-31',
  },
  orderBy: { field: 'orderSum', mode: 'desc' },
  limit: 20,
  offset: 0,
  skipDeletedNm: true,
});

for (const entry of report.products) {
  const { product, statistic } = entry;
  const current = statistic.selected;
  console.log(
    `${product.title} (nmId: ${product.nmId})`,
    `| Views: ${current.openCount}`,
    `| Cart: ${current.cartCount}`,
    `| Orders: ${current.orderCount} (${current.orderSum} ${report.currency})`,
    `| Buyout: ${current.buyoutCount} (${current.conversions.buyoutPercent}%)`,
  );

  // Period-over-period comparison (available when pastPeriod is provided)
  if (statistic.comparison) {
    console.log(
      `  Delta: orders ${statistic.comparison.orderCountDynamic > 0 ? '+' : ''}${statistic.comparison.orderCountDynamic}%`,
      `| buyouts ${statistic.comparison.buyoutCountDynamic > 0 ? '+' : ''}${statistic.comparison.buyoutCountDynamic}%`,
    );
  }
}

Request parameters:

Parameter	Type	Required	Description
selectedPeriod	DatePeriod	Yes	Start and end dates (YYYY-MM-DD) for the report
pastPeriod	DatePeriod	No	Comparison period. When provided, response includes comparison deltas
nmIds	number[]	No	Filter by WB article IDs
brandNames	string[]	No	Filter by brand names
subjectIds	number[]	No	Filter by subject (category) IDs
tagIds	number[]	No	Filter by tag IDs
skipDeletedNm	boolean	No	Exclude deleted product cards from results
orderBy	SalesFunnelOrderBy	No	Sort field and direction (asc or desc)
limit	number	No	Number of products per page
offset	number	No	Number of products to skip (for pagination)

getSalesFunnelProductsHistory -- Daily/Weekly Breakdown

Returns day-by-day or week-by-week statistics for specific products. Use this method to track how individual product metrics change over time.

Period limit: maximum 7 days.

Note: The nmIds parameter is required for this method.

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

const history = await sdk.analytics.getSalesFunnelProductsHistory({
  selectedPeriod: {
    start: '2026-03-22',
    end: '2026-03-28',
  },
  nmIds: [268913787],
  aggregationLevel: 'day',
  skipDeletedNm: true,
});

// Response is an array -- one element per product
for (const item of history) {
  console.log(`Product: ${item.product.title} (nmId: ${item.product.nmId})`);

  for (const day of item.history) {
    console.log(
      `  ${day.date}`,
      `| Views: ${day.openCount}`,
      `| Cart: ${day.cartCount} (${day.addToCartConversion}%)`,
      `| Orders: ${day.orderCount} (${day.cartToOrderConversion}%)`,
      `| Buyout: ${day.buyoutCount} (${day.buyoutPercent}%)`,
    );
  }
}

Request parameters:

Parameter	Type	Required	Description
selectedPeriod	DatePeriod	Yes	Start and end dates (max 7-day span)
nmIds	number[]	Yes	WB article IDs to retrieve history for
skipDeletedNm	boolean	No	Exclude deleted product cards
aggregationLevel	'day' | 'week'	No	Granularity of the breakdown. Defaults to 'day'

getSalesFunnelGroupedHistory -- Grouped by Category/Brand/Tag

Returns daily or weekly statistics grouped by subjects, brands, or tags rather than individual products. Use this to analyze performance trends at the category or brand level.

Period limit: maximum 7 days.

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

const grouped = await sdk.analytics.getSalesFunnelGroupedHistory({
  selectedPeriod: {
    start: '2026-03-22',
    end: '2026-03-28',
  },
  subjectIds: [105],       // e.g., "T-shirts" category
  aggregationLevel: 'day',
  skipDeletedNm: true,
});

for (const group of grouped) {
  console.log(`Group: ${group.product.subjectName} / ${group.product.brandName}`);
  for (const day of group.history) {
    console.log(
      `  ${day.date}: ${day.orderCount} orders, ${day.buyoutPercent}% buyout`,
    );
  }
}

Request parameters:

Parameter	Type	Required	Description
selectedPeriod	DatePeriod	Yes	Start and end dates (max 7-day span)
brandNames	string[]	No	Filter by brand names
subjectIds	number[]	No	Filter by subject (category) IDs
tagIds	number[]	No	Filter by tag IDs
skipDeletedNm	boolean	No	Exclude deleted product cards
aggregationLevel	'day' | 'week'	No	Granularity of the breakdown. Defaults to 'day'

---

Key Metrics Reference

Funnel Volume Metrics

Metric	Type	Description
openCount	number	Product card views (impressions)
cartCount	number	Times the product was added to cart
orderCount	number	Number of orders placed
orderSum	number	Total monetary value of orders
buyoutCount	number	Number of completed purchases (kept by customer)
buyoutSum	number	Total monetary value of buyouts
cancelCount	number	Number of cancelled orders
cancelSum	number	Total monetary value of cancellations

Conversion Metrics

The conversions object contains the three stage-to-stage conversion rates:

Metric	Type	Description
addToCartPercent	number	Percentage of viewers who added the product to cart
cartToOrderPercent	number	Percentage of cart additions that converted to orders
buyoutPercent	number	Percentage of orders that were completed as purchases

Pricing and Revenue

Metric	Type	Description
avgPrice	number	Average selling price for the period
avgOrdersCountPerDay	number	Average number of orders per day
shareOrderPercent	number	Product's share of total seller revenue

Engagement and Logistics

Metric	Type	Description
addToWishlist	number	Times the product was added to the Wishlist
timeToReady	SalesFunnelTimeToReady	Average delivery time (days, hours, minutes)
localizationPercent	number	Percentage of orders that are intra-regional (same region as warehouse)

WB Club Metrics

The wbClub object contains metrics specifically for orders placed by WB Club members:

Metric	Type	Description
wbClub.orderCount	number	Orders from WB Club members
wbClub.orderSum	number	Order value from WB Club members
wbClub.buyoutCount	number	Buyouts by WB Club members
wbClub.buyoutSum	number	Buyout value from WB Club members
wbClub.buyoutPercent	number	Buyout rate for WB Club members
wbClub.avgOrderCountPerDay	number	Average daily orders from WB Club

History-Specific Metrics

The daily/weekly history endpoints (getSalesFunnelProductsHistory and getSalesFunnelGroupedHistory) return SalesFunnelHistory records with these fields per time period:

Field	Type	Description
date	string	Date of the data point
openCount	number	Views for that day/week
cartCount	number	Cart additions
orderCount	number	Orders placed
orderSum	number	Order value
buyoutCount	number	Completed purchases
buyoutSum	number	Buyout value
buyoutPercent	number	Buyout rate
addToCartConversion	number	View-to-cart conversion rate
cartToOrderConversion	number	Cart-to-order conversion rate
addToWishlistCount	number	Wishlist additions

---

Filtering and Sorting

Filter Parameters

All three methods support filtering to narrow down the dataset. The summary method (getSalesFunnelProducts) supports all filters; the history methods support a subset.

nmIds -- Filter by WB Article

Pass an array of Wildberries article numbers to retrieve data for specific products. This is the most common filter when you want to monitor a known set of SKUs.

// Monitor your top 5 products
const report = await sdk.analytics.getSalesFunnelProducts({
  selectedPeriod: { start: '2026-03-01', end: '2026-03-28' },
  nmIds: [268913787, 395996251, 112334455, 998877665, 554433221],
});

Supported by: getSalesFunnelProducts, getSalesFunnelProductsHistory

brandNames -- Filter by Brand

Useful when your seller account manages multiple brands and you want to analyze brand-level performance.

const report = await sdk.analytics.getSalesFunnelProducts({
  selectedPeriod: { start: '2026-03-01', end: '2026-03-28' },
  brandNames: ['MyBrand', 'SecondBrand'],
  orderBy: { field: 'orderSum', mode: 'desc' },
  limit: 50,
  offset: 0,
});

Supported by: getSalesFunnelProducts, getSalesFunnelGroupedHistory

subjectIds -- Filter by Subject (Category)

Subject IDs correspond to Wildberries product categories (e.g., T-shirts, Sneakers). Use this when comparing performance across categories.

const grouped = await sdk.analytics.getSalesFunnelGroupedHistory({
  selectedPeriod: { start: '2026-03-22', end: '2026-03-28' },
  subjectIds: [105, 210],   // Two categories
  aggregationLevel: 'day',
});

Supported by: getSalesFunnelProducts, getSalesFunnelGroupedHistory

tagIds -- Filter by Tag

Tags are seller-defined labels assigned to products in the Wildberries seller portal. Use this to segment analytics by your own organizational structure (e.g., "Summer Collection", "Clearance").

const report = await sdk.analytics.getSalesFunnelProducts({
  selectedPeriod: { start: '2026-03-01', end: '2026-03-28' },
  tagIds: [42],   // "Summer Collection" tag
  orderBy: { field: 'buyoutCount', mode: 'desc' },
  limit: 100,
  offset: 0,
});

Supported by: getSalesFunnelProducts, getSalesFunnelGroupedHistory

skipDeletedNm -- Exclude Deleted Cards

When set to true, products that have been deleted from your catalog are excluded from results. This keeps your analytics clean when products are discontinued.

Supported by: all three methods.

Sorting (getSalesFunnelProducts only)

The orderBy parameter controls the sort order of the paginated result set. It accepts a field and a mode ('asc' or 'desc').

Available sort fields:

Field	Description
openCard	Sort by product card views
addToCart	Sort by cart additions
orderCount	Sort by order quantity
orderSum	Sort by order revenue
buyoutCount	Sort by buyout quantity
buyoutSum	Sort by buyout revenue
cancelCount	Sort by cancellations
cancelSum	Sort by cancellation value
avgPrice	Sort by average price
stockMpQty	Sort by seller warehouse stock
stockWbQty	Sort by WB warehouse stock
shareOrderPercent	Sort by revenue share
addToWishlist	Sort by wishlist additions
timeToReady	Sort by delivery time
localizationPercent	Sort by regional order percentage

WB Club fields are also available with the wbClub. prefix (e.g., wbClub.orderCount, wbClub.buyoutPercent).

---

Practical Scenarios

ABC Analysis of Product Assortment

ABC analysis classifies products into three groups by their contribution to total revenue. Group A products generate roughly 80% of revenue, Group B the next 15%, and Group C the remaining 5%.

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

async function abcAnalysis(startDate: string, endDate: string) {
  // Fetch all products sorted by revenue descending
  const allProducts: Array<{
    nmId: number;
    title: string;
    revenue: number;
    buyoutPercent: number;
  }> = [];

  let offset = 0;
  const pageSize = 100;
  let hasMore = true;

  while (hasMore) {
    const page = await sdk.analytics.getSalesFunnelProducts({
      selectedPeriod: { start: startDate, end: endDate },
      orderBy: { field: 'buyoutSum', mode: 'desc' },
      limit: pageSize,
      offset,
      skipDeletedNm: true,
    });

    for (const entry of page.products) {
      allProducts.push({
        nmId: entry.product.nmId,
        title: entry.product.title,
        revenue: entry.statistic.selected.buyoutSum,
        buyoutPercent: entry.statistic.selected.conversions.buyoutPercent,
      });
    }

    hasMore = page.products.length === pageSize;
    offset += pageSize;
  }

  // Calculate cumulative revenue share
  const totalRevenue = allProducts.reduce((sum, p) => sum + p.revenue, 0);
  let cumulativeShare = 0;

  const classified = allProducts.map((product) => {
    cumulativeShare += product.revenue / totalRevenue;
    let group: 'A' | 'B' | 'C';
    if (cumulativeShare <= 0.8) {
      group = 'A';
    } else if (cumulativeShare <= 0.95) {
      group = 'B';
    } else {
      group = 'C';
    }
    return { ...product, group };
  });

  // Summary
  const groups = { A: 0, B: 0, C: 0 };
  for (const item of classified) {
    groups[item.group]++;
  }

  console.log(`ABC Analysis for ${startDate} to ${endDate}:`);
  console.log(`  Total products: ${classified.length}`);
  console.log(`  Total revenue: ${totalRevenue.toLocaleString()}`);
  console.log(`  Group A: ${groups.A} products (80% of revenue)`);
  console.log(`  Group B: ${groups.B} products (next 15%)`);
  console.log(`  Group C: ${groups.C} products (remaining 5%)`);

  return classified;
}

const result = await abcAnalysis('2026-01-01', '2026-03-28');

Comparing Conversion Rates Across Periods

Identify whether your conversion metrics are improving or declining by comparing the current month against the previous month.

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

async function compareConversions() {
  const report = await sdk.analytics.getSalesFunnelProducts({
    selectedPeriod: {
      start: '2026-03-01',
      end: '2026-03-28',
    },
    pastPeriod: {
      start: '2026-02-01',
      end: '2026-02-28',
    },
    orderBy: { field: 'orderSum', mode: 'desc' },
    limit: 50,
    offset: 0,
    skipDeletedNm: true,
  });

  console.log('Product Conversion Comparison (March vs February):');
  console.log('---------------------------------------------------');

  for (const entry of report.products) {
    const { product, statistic } = entry;
    const current = statistic.selected.conversions;
    const past = statistic.past?.conversions;

    console.log(`\n${product.title} (${product.nmId}):`);
    console.log(`  Add-to-cart:    ${current.addToCartPercent}%`);
    console.log(`  Cart-to-order:  ${current.cartToOrderPercent}%`);
    console.log(`  Buyout:         ${current.buyoutPercent}%`);

    if (past) {
      const cartDelta = current.addToCartPercent - past.addToCartPercent;
      const orderDelta = current.cartToOrderPercent - past.cartToOrderPercent;
      const buyoutDelta = current.buyoutPercent - past.buyoutPercent;

      console.log(`  vs. past period:`);
      console.log(`    Add-to-cart:   ${cartDelta > 0 ? '+' : ''}${cartDelta.toFixed(1)}pp`);
      console.log(`    Cart-to-order: ${orderDelta > 0 ? '+' : ''}${orderDelta.toFixed(1)}pp`);
      console.log(`    Buyout:        ${buyoutDelta > 0 ? '+' : ''}${buyoutDelta.toFixed(1)}pp`);
    }
  }
}

await compareConversions();

Tracking Daily Trends for a Product

Monitor a specific product's performance day-by-day to detect sudden changes or the impact of promotions.

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

async function trackDailyTrends(nmId: number) {
  const history = await sdk.analytics.getSalesFunnelProductsHistory({
    selectedPeriod: {
      start: '2026-03-22',
      end: '2026-03-28',
    },
    nmIds: [nmId],
    aggregationLevel: 'day',
    skipDeletedNm: true,
  });

  if (history.length === 0) {
    console.log(`No data found for nmId ${nmId}`);
    return;
  }

  const item = history[0];
  console.log(`Daily trends for: ${item.product.title}`);
  console.log(`Period: ${item.history[0]?.date} to ${item.history[item.history.length - 1]?.date}`);
  console.log('');

  // Calculate averages
  const days = item.history;
  const avgViews = days.reduce((s, d) => s + d.openCount, 0) / days.length;
  const avgOrders = days.reduce((s, d) => s + d.orderCount, 0) / days.length;

  console.log(`  Average daily views:  ${avgViews.toFixed(0)}`);
  console.log(`  Average daily orders: ${avgOrders.toFixed(1)}`);
  console.log('');

  // Day-by-day breakdown
  for (const day of days) {
    const viewsVsAvg = ((day.openCount - avgViews) / avgViews * 100).toFixed(0);
    const marker = Math.abs(Number(viewsVsAvg)) > 30 ? ' <-- significant change' : '';

    console.log(
      `  ${day.date}:`,
      `Views: ${day.openCount} (${Number(viewsVsAvg) > 0 ? '+' : ''}${viewsVsAvg}% vs avg)`,
      `| Cart: ${day.addToCartConversion}%`,
      `| Orders: ${day.orderCount}`,
      `| Buyout: ${day.buyoutPercent}%`,
      marker,
    );
  }
}

await trackDailyTrends(268913787);

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CSV Reports for Extended Periods

The three JSON-based sales funnel methods described above are limited to 365 days (summary) or 7 days (history). For longer time ranges or very large datasets, use the CSV report endpoints instead.

CSV reports are generated asynchronously. You create a report generation task, poll for its status, and then download the resulting ZIP archive containing a CSV file.

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

// Step 1: Create a report generation task
const task = await sdk.analytics.createNmReportDownload({
  reportType: 'SALES_FUNNEL_PRODUCT',
  userReportName: 'Q1 2026 Sales Funnel',
  params: {
    selectedPeriod: {
      start: '2026-01-01',
      end: '2026-03-31',
    },
    aggregationLevel: 'month',
    skipDeletedNm: true,
  },
});

console.log('Report task created:', task.data?.downloadId);

CSV reports require a Jam subscription for certain report types. If you need to detect your subscription tier before making requests, see the Jam Subscription Detection guide.

For a complete walkthrough of the CSV report workflow (creation, polling, download, and parsing), see the Seller Analytics CSV Reports guide.

---

Rate Limits

All three sales funnel methods share the same rate limit:

• 3 requests per minute
• 20-second interval between requests
• Burst limit: 3 requests

The SDK enforces these limits automatically through its built-in rate limiter. If you exceed the limit, the SDK throws a RateLimitError with retry timing information.

When paginating through large datasets, add a brief delay between pages:

const delay = (ms: number) => new Promise((resolve) => setTimeout(resolve, ms));

let offset = 0;
const pageSize = 100;

while (true) {
  const page = await sdk.analytics.getSalesFunnelProducts({
    selectedPeriod: { start: '2026-01-01', end: '2026-03-28' },
    orderBy: { field: 'orderSum', mode: 'desc' },
    limit: pageSize,
    offset,
  });

  // Process page...

  if (page.products.length < pageSize) break;
  offset += pageSize;

  // Respect the 20-second interval
  await delay(20_000);
}

---

Error Handling

import { WildberriesSDK } from 'daytona-wildberries-typescript-sdk';
import {
  RateLimitError,
  AuthenticationError,
  ValidationError,
} from 'daytona-wildberries-typescript-sdk';

const sdk = new WildberriesSDK({ apiKey: process.env.WB_API_KEY! });

try {
  const report = await sdk.analytics.getSalesFunnelProducts({
    selectedPeriod: { start: '2026-03-01', end: '2026-03-28' },
    limit: 20,
    offset: 0,
  });
  // Process report...
} catch (error) {
  if (error instanceof RateLimitError) {
    console.error(`Rate limited. Retry after ${error.retryAfter}ms`);
  } else if (error instanceof AuthenticationError) {
    console.error('Invalid API key. Check your credentials.');
  } else if (error instanceof ValidationError) {
    console.error('Invalid request parameters:', error.message);
  } else {
    throw error;
  }
}

Common validation errors:

• Period exceeds maximum: The summary endpoint allows up to 365 days; the history endpoints allow up to 7 days. Exceeding these limits returns a 400 error.
• Missing required nmIds: The getSalesFunnelProductsHistory method requires at least one nmId.
• Invalid date format: Dates must be in YYYY-MM-DD format.

---

Related Resources

• Analytics Module Reference -- Full API reference for all analytics methods
• Sales Funnel Analytics Best Practices -- Optimization strategies combining organic and advertising funnel data
• Jam Subscription Detection -- Detect your Jam tier for correct analytics limits
• Production Best Practices -- Error handling, rate limiting, and deployment patterns