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feat(报告): 第六章增加优惠活动与标价券后价差分析
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@ -281,6 +281,198 @@ def _collect_prices(rows: list[dict[str, str]]) -> list[float]:
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return out
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_JD_LIST_PRICE_KEY = "标价(jdPrice,jdPriceText,realPrice)"
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_COUPON_SHOW_PRICE_KEY = (
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"券后到手价(couponPrice,subsidyPrice,finalPrice.estimatedPrice,priceShow)"
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)
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_ORIGINAL_LIST_PRICE_KEY = "原价(oriPrice,originalPrice,marketPrice)"
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_SELLING_POINT_KEY = "卖点(sellingPoint)"
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_RANK_TAGLINE_KEY = "榜单类文案(标签/腰带/标题数组中的榜、TOP 等)"
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# 列表/合并表中「卖点、腰带」常见活动话术子串（行级命中，非严谨 NLP）
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_PROMO_SUBSTRINGS_IN_COPY: tuple[str, ...] = (
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"满减",
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"秒杀",
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"限时",
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"优惠券",
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"领券",
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"券后",
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"百亿补贴",
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"包邮",
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"赠品",
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"买赠",
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"第二件",
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"第2件",
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"直降",
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"特价",
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"促销",
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"套装",
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"任选",
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"到手价",
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"补贴",
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"聚划算",
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"预售",
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"定金",
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"返现",
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"折扣",
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"加购",
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"下单立减",
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)
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def _analyze_price_promotions(rows: list[dict[str, str]]) -> dict[str, Any]:
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"""
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从列表或合并行中归纳「标价 vs 券后/到手」及卖点/腰带中的活动话术信号，
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供 §6.1 与结构化摘要使用（**页面展示口径**，非结算实付）。
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"""
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n = len(rows)
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with_jd = with_cp = with_both = 0
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coupon_below = 0
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pct_offs: list[float] = []
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ori_above_list = 0
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for row in rows:
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jd = _float_price(_cell(row, _JD_LIST_PRICE_KEY))
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cp = _float_price(_cell(row, _COUPON_SHOW_PRICE_KEY))
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ori = _float_price(_cell(row, _ORIGINAL_LIST_PRICE_KEY))
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if jd is not None and jd > 0:
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with_jd += 1
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if cp is not None and cp > 0:
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with_cp += 1
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if jd is not None and cp is not None and jd > 0 and cp > 0:
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with_both += 1
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if cp + 1e-6 < jd:
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coupon_below += 1
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pct_offs.append((jd - cp) / jd * 100.0)
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if (
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ori is not None
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and jd is not None
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and ori > 0
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and jd > 0
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and ori > jd + 1e-6
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):
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ori_above_list += 1
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selling_nonempty = sum(
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1 for r in rows if _cell(r, _SELLING_POINT_KEY).strip()
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)
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rank_nonempty = sum(1 for r in rows if _cell(r, _RANK_TAGLINE_KEY).strip())
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kw_row_hits: dict[str, int] = {}
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for kw in _PROMO_SUBSTRINGS_IN_COPY:
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c = 0
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for row in rows:
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blob = (
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_cell(row, _SELLING_POINT_KEY) + " " + _cell(row, _RANK_TAGLINE_KEY)
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)
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if kw in blob:
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c += 1
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if c:
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kw_row_hits[kw] = c
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top_promos = sorted(kw_row_hits.items(), key=lambda x: -x[1])[:14]
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median_pct = statistics.median(pct_offs) if pct_offs else None
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mean_pct = statistics.mean(pct_offs) if pct_offs else None
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share_below = (
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(coupon_below / with_both) if with_both else None
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)
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return {
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"row_count": n,
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"rows_with_list_price": with_jd,
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"rows_with_coupon_price": with_cp,
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"rows_with_both_list_and_coupon": with_both,
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"rows_coupon_below_list_price": coupon_below,
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"share_coupon_below_list_when_both": share_below,
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"median_discount_pct_when_coupon_below": median_pct,
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"mean_discount_pct_when_coupon_below": mean_pct,
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"rows_original_price_above_list_price": ori_above_list,
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"rows_selling_point_nonempty": selling_nonempty,
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"rows_rank_tagline_nonempty": rank_nonempty,
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"promo_keyword_row_hits_top": [
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{"keyword": k, "rows": v} for k, v in top_promos
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],
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}
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def _markdown_price_promotion_section(p: dict[str, Any]) -> list[str]:
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"""§6.1 优惠活动与价差信号（Markdown 行列表）。"""
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lines: list[str] = [
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"### 6.1 优惠活动与价差信号（页面展示摘录）",
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"",
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"- **口径**：与上节价量统计**同一批行**；比较的是列表/合并表中的**展示标价**与**展示券后/到手价**（字段见表头），"
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"反映页面呈现的活动与券信息，**不等于**用户结算实付或历史最低价。",
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"",
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]
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wb = int(p.get("rows_with_both_list_and_coupon") or 0)
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if wb <= 0:
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lines.append(
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"- **标价与券后价可对齐比较**的有效行不足，本节仅摘录卖点/腰带中的活动话术（若有）。"
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)
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lines.append("")
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else:
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cb = int(p.get("rows_coupon_below_list_price") or 0)
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sh = p.get("share_coupon_below_list_when_both")
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med = p.get("median_discount_pct_when_coupon_below")
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mean = p.get("mean_discount_pct_when_coupon_below")
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lines.append(
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f"- **同时解析到标价与券后/到手价** 的行：**{wb}**；其中展示「到手/券后」**严格低于**「标价」的行：**{cb}**"
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+ (
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f"（占可对齐行的 **{100.0 * float(sh):.1f}%**）"
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if isinstance(sh, (int, float))
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else ""
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)
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+ "。"
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)
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if med is not None:
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frag_mean = (
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f"，平均价差约 **{float(mean):.1f}%**" if mean is not None else ""
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)
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lines.append(
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f"- **价差力度（仅「券后低于标价」子集）**：展示价差的中位数约 **{float(med):.1f}%**（相对标价）{frag_mean}；"
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"通常对应满减、券、限时价等在列表上的叠加呈现。"
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)
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elif cb > 0:
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lines.append(
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"- **价差**：存在「券后低于标价」样本，但条数较少，未给出稳健分位数；建议结合 §5 单品对照。"
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)
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lines.append("")
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oa = int(p.get("rows_original_price_above_list_price") or 0)
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if oa > 0:
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lines.append(
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f"- **划线原价高于当前标价** 的行约 **{oa}** 条（常见「划线价 + 当前价」促销陈列，具体以页面为准）。"
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)
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lines.append("")
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sn = int(p.get("rows_selling_point_nonempty") or 0)
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rn = int(p.get("rows_rank_tagline_nonempty") or 0)
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nr = int(p.get("row_count") or 0)
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if nr > 0:
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lines.append(
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f"- **卖点字段非空**：**{sn}** / **{nr}** 行；**榜单/腰带类文案非空**：**{rn}** / **{nr}** 行（用于观察申报活动与心智标签）。"
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)
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lines.append("")
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top = p.get("promo_keyword_row_hits_top") or []
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if isinstance(top, list) and top:
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lines.append("- **活动话术在列表行中的出现面**（卖点+腰带合并扫描预设子串；**同一行可含多词**，为行级命中次数）：")
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parts = []
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for it in top[:10]:
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if isinstance(it, dict):
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k = it.get("keyword") or ""
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v = it.get("rows")
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if k and v is not None:
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parts.append(f"「{k}」**{int(v)}** 行")
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if parts:
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lines.append(" - " + "；".join(parts) + "。")
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lines.append(
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" - **解读**：高频词反映列表侧**主推活动类型**（如满减、百亿补贴、赠品）；与 §6 分布表结合看「低价来自常态价还是大促价带」。"
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)
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else:
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lines.append(
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"- **活动话术**：未在卖点/腰带字段中命中预设促销子串（可能字段为空或话术与词表不一致）。"
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)
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lines.append("")
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return lines
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def _comment_keyword_hits(
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rows: list[dict[str, str]],
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focus_words: tuple[str, ...],
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@ -1275,6 +1467,12 @@ def build_competitor_markdown(
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if list_export and pst_list.get("n", 0) > 0
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else f"已深入抓取的 **{n_sku}** 个 SKU 合并数据中的展示价"
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)
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promo_rows = (
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search_export_rows
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if list_export and pst_list.get("n", 0) > 0
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else merged_rows
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)
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promo_sig = _analyze_price_promotions(promo_rows)
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hits = _comment_keyword_hits(comment_rows, focus_words)
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if not hits:
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@ -1341,7 +1539,7 @@ def build_competitor_markdown(
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"",
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"### 1.3 方法说明（指标含义）",
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"",
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"- **价格**：自页面「标价 / 券后价 / 详情价」等抽取的**展示价**，含促销与规格差异，**不等于**出厂价或成本。**第六章** 在具备可用的搜索列表导出时，优先以**列表全量**统计；否则使用**已深入 SKU** 的合并数据。",
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"- **价格**：自页面「标价 / 券后价 / 详情价」等抽取的**展示价**，含促销与规格差异，**不等于**出厂价或成本。**第六章** 在具备可用的搜索列表导出时，优先以**列表全量**统计；否则使用**已深入 SKU** 的合并数据；**§6.1** 归纳标价与券后价差及卖点/腰带中的**活动话术信号**。",
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"- **品牌/店铺集中度（第四章）**：有列表全量时按列表行计店铺与品牌占比；无列表导出时按深入 SKU 合并表估算。",
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"- **评价主题词**：对评价正文做**预设词表子串计数**，非分词主题模型，适合扫方向，**需抽样人工验证**。",
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"- **用途/场景**：对每条评价独立判断是否命中预设场景词；一条可计入多个场景，统计的是「提及该场景的评价条数」而非用户数。",
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@ -1420,6 +1618,13 @@ def build_competitor_markdown(
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f"展示价格{price_src_short}：可解析价格 **{pst['n']}** 个观测，区间约 **{pst['min']:.2f}～{pst['max']:.2f}** 元，"
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f"中位数 **{pst.get('median', pst['mean']):.2f}** 元。"
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)
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wb = int(promo_sig.get("rows_with_both_list_and_coupon") or 0)
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sh = promo_sig.get("share_coupon_below_list_when_both")
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med = promo_sig.get("median_discount_pct_when_coupon_below")
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if wb >= 3 and isinstance(sh, (int, float)) and sh >= 0.08 and med is not None:
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exec_bullets.append(
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f"列表侧约 **{100.0 * float(sh):.0f}%** 可对齐行呈现「券后/到手」**低于**「标价」，展示价差中位数约 **{float(med):.1f}%**（**§6.1** 活动与话术摘录）。"
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)
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if multi_feedback_cat and (hits or scen_n_texts > 0):
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exec_bullets.append(
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"评价侧写（关注词、用途/场景）已按 **§5 同款细类** 分节，见 **§8.3～8.4**。"
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@ -1736,8 +1941,12 @@ def build_competitor_markdown(
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lines.append(
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"**解读提示**：价差大通常反映规格、组合装、品牌溢价或促销差异；B 端定价策略需结合成本与渠道单独建模。"
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)
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lines.append("")
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lines.extend(_markdown_price_promotion_section(promo_sig))
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else:
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lines.append("*当前样本无可用数值价格，本节不展开统计表。*")
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lines.append("")
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lines.extend(_markdown_price_promotion_section(promo_sig))
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lines.append("")
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attrs: list[str] = []
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@ -2007,6 +2216,12 @@ def build_competitor_brief(
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if list_export and pst_list.get("n", 0) > 0
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else "keyword_pipeline_merged"
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)
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promo_rows_brief = (
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search_export_rows
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if list_export and pst_list.get("n", 0) > 0
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else merged_rows
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)
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price_promotion_signals = _analyze_price_promotions(promo_rows_brief)
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hits = _comment_keyword_hits(comment_rows, focus_words)
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if not hits:
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@ -2206,6 +2421,7 @@ def build_competitor_brief(
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"price_stats_source": price_stats_source,
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"price_stats_merged_sample": pst_merged,
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"price_stats_list_export": pst_list if list_export else {},
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"price_promotion_signals": price_promotion_signals,
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"comment_focus_keywords": [
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{"word": w, "count": n} for w, n in hits.most_common(24)
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],
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@ -2227,7 +2443,7 @@ def build_competitor_brief(
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"comment_sentiment_lexicon": comment_sentiment_lexicon,
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"notes": [
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"与在线分析报告各章统计口径一致；主题词与场景为预设词表，非 NLP 主题模型。",
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"价格来自页面展示字段抽取，含促销与规格差异。",
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"价格来自页面展示字段抽取，含促销与规格差异；price_promotion_signals 为标价/券后对齐与卖点话术的启发式摘录。",
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"comment_sentiment_lexicon 为关键词粗判，非深度学习情感模型。",
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],
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}
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