# -*- coding: utf-8 -*- """Generate Taobao mini-program product proposal PPTX (no company name). 注意：这一份是更早的版本（输出 AI智能测肤-淘宝小程序产品方案.pptx，当前仓库里没有该成品）， 保留用于追溯版式。现行版本见 build_taobao_proposal_from_template.py / build_taobao_proposal_dark.py。 """ from pathlib import Path from pptx import Presentation from pptx.util import Emu, Pt from pptx.dml.color import RGBColor from pptx.enum.shapes import MSO_SHAPE from pptx.enum.text import PP_ALIGN from pptx.oxml.ns import qn from lxml import etree OUT = str(Path(__file__).resolve().parents[1] / "AI智能测肤-淘宝小程序产品方案.pptx") W, H = 24384000, 13716000 # 16:9 BG = RGBColor(0x0F, 0x1A, 0x26) BG_CARD = RGBColor(0x18, 0x27, 0x38) ACCENT = RGBColor(0x2E, 0xC4, 0xB6) WHITE = RGBColor(0xFF, 0xFF, 0xFF) MUTED = RGBColor(0xA8, 0xB4, 0xC0) LINE = RGBColor(0x2A, 0x3B, 0x4F) TITLE = RGBColor(0xF2, 0xF6, 0xFA) PANEL = RGBColor(0x14, 0x2A, 0x3C) def set_run(run, size=18, bold=False, color=WHITE, font="微软雅黑"): run.font.size = Pt(size) run.font.bold = bold run.font.color.rgb = color run.font.name = font rPr = run._r.get_or_add_rPr() ea = rPr.find(qn("a:ea")) if ea is None: ea = etree.SubElement(rPr, qn("a:ea")) ea.set("typeface", font) def add_bg(slide, color=BG): shape = slide.shapes.add_shape(MSO_SHAPE.RECTANGLE, 0, 0, W, H) shape.fill.solid() shape.fill.fore_color.rgb = color shape.line.fill.background() spTree = slide.shapes._spTree sp = shape._element spTree.remove(sp) spTree.insert(2, sp) def add_bar(slide, left, top, width=Emu(457200), height=Emu(70000)): bar = slide.shapes.add_shape(MSO_SHAPE.RECTANGLE, left, top, width, height) bar.fill.solid() bar.fill.fore_color.rgb = ACCENT bar.line.fill.background() def add_text(slide, left, top, width, height, text, size=18, bold=False, color=WHITE, align=PP_ALIGN.LEFT): box = slide.shapes.add_textbox(left, top, width, height) tf = box.text_frame tf.word_wrap = True p = tf.paragraphs[0] p.alignment = align run = p.add_run() run.text = text set_run(run, size=size, bold=bold, color=color) return box def add_paras(slide, left, top, width, height, lines, size=15, color=MUTED, bold=False, gap=10): box = slide.shapes.add_textbox(left, top, width, height) tf = box.text_frame tf.word_wrap = True for i, line in enumerate(lines): p = tf.paragraphs[0] if i == 0 else tf.add_paragraph() p.alignment = PP_ALIGN.LEFT p.space_after = Pt(gap) run = p.add_run() run.text = line set_run(run, size=size, bold=bold, color=color) return box def add_card(slide, left, top, width, height): card = slide.shapes.add_shape(MSO_SHAPE.ROUNDED_RECTANGLE, left, top, width, height) card.fill.solid() card.fill.fore_color.rgb = BG_CARD card.line.color.rgb = LINE card.line.width = Pt(1) return card def blank(prs): return prs.slides.add_slide(prs.slide_layouts[6]) def section_title(slide, num, title): add_bg(slide) add_text(slide, Emu(914400), Emu(420000), Emu(2000000), Emu(450000), num, size=28, bold=True, color=ACCENT) add_text(slide, Emu(1600200), Emu(450000), Emu(14000000), Emu(450000), title, size=28, bold=True, color=TITLE) add_bar(slide, Emu(914400), Emu(950000)) def build(): prs = Presentation() prs.slide_width = W prs.slide_height = H # ---- 1 Cover ---- s = blank(prs) add_bg(s) panel = s.shapes.add_shape(MSO_SHAPE.RECTANGLE, 0, 0, Emu(3200400), H) panel.fill.solid() panel.fill.fore_color.rgb = PANEL panel.line.fill.background() add_bar(s, Emu(4000500), Emu(4200000), Emu(914400), Emu(90000)) add_text(s, Emu(4000500), Emu(4500000), Emu(17000000), Emu(900000), "AI 智能测肤", size=44, bold=True, color=TITLE) add_text(s, Emu(4000500), Emu(5450000), Emu(17000000), Emu(700000), "淘宝小程序产品方案", size=32, bold=True, color=ACCENT) add_text(s, Emu(4000500), Emu(6350000), Emu(17000000), Emu(500000), "在线肌肤检测 · 个性化护理建议 · 精准商品推荐", size=16, color=MUTED) add_text(s, Emu(4000500), Emu(11000000), Emu(8000000), Emu(400000), "自研类型申请材料", size=12, color=MUTED) # ---- 2 Product positioning (replaces company background) ---- s = blank(prs) add_bg(s) add_bar(s, Emu(914400), Emu(685800)) add_text(s, Emu(914400), Emu(420000), Emu(16000000), Emu(500000), "产品定位", size=28, bold=True, color=TITLE) add_text(s, Emu(914400), Emu(1200000), Emu(20000000), Emu(600000), "面向淘宝美妆消费者的「检测—报告—推荐—购买」一站式肌肤服务小程序", size=18, color=MUTED) cards = [ ("核心能力", "基于面部图像的 AI 肌肤分析，输出综合评分、肌龄、七项分项结论与护理建议。"), ("转化路径", "报告结果直接关联店铺商品，按肌龄与肤质状态推荐适配精华，缩短决策路径。"), ("适用场景", "品牌旗舰店导购、直播/详情页引流、会员复购关怀、线下到线上测肤体验延伸。"), ("差异价值", "不是通用展示页，而是可闭环的「测肤服务 + 商品转化」能力，补足平台现有内容与货架之间的决策缺口。"), ] for i, (t, d) in enumerate(cards): col = i % 2 row = i // 2 left = Emu(914400 + col * 11000000) top = Emu(2100000 + row * 4200000) add_card(s, left, top, Emu(10000000), Emu(3600000)) add_text(s, left + Emu(400000), top + Emu(350000), Emu(9000000), Emu(500000), t, size=18, bold=True, color=ACCENT) add_text(s, left + Emu(400000), top + Emu(1000000), Emu(9000000), Emu(2200000), d, size=15, color=MUTED) # ---- 3 TOC ---- s = blank(prs) add_bg(s) add_text(s, Emu(914400), Emu(420000), Emu(8000000), Emu(500000), "目录", size=32, bold=True, color=TITLE) add_bar(s, Emu(914400), Emu(1000000)) toc = [ ("01", "市场调研分析"), ("02", "小程序方案及价值"), ("03", "商业化运营规划及目标"), ] for i, (num, name) in enumerate(toc): top = Emu(2200000 + i * 2200000) circle = s.shapes.add_shape(MSO_SHAPE.OVAL, Emu(914400), top, Emu(1100000), Emu(1100000)) circle.fill.solid() circle.fill.fore_color.rgb = ACCENT circle.line.fill.background() add_text(s, Emu(914400), top + Emu(280000), Emu(1100000), Emu(600000), num, size=22, bold=True, color=BG, align=PP_ALIGN.CENTER) add_text(s, Emu(2400000), top + Emu(300000), Emu(12000000), Emu(600000), name, size=26, bold=True, color=TITLE) # ---- 4 Market research ---- s = blank(prs) section_title(s, "01", "市场调研分析") add_paras(s, Emu(914400), Emu(1300000), Emu(22000000), Emu(11000000), [ "1）商家价值与痛点 / 消费者诉求", "· 商家痛点：美妆选品高度依赖经验，线上货架信息多、决策成本高，难以把「适合我」讲清楚；直播与详情页流量难沉淀为可复访服务。", "· 消费者诉求：想知道自己肤质与肌龄、哪里需要改善、该买哪一支精华；希望少踩雷、有依据、可即时下单。", "· 本方案以测肤报告建立信任，再以肌龄分档推荐商品，同时满足「专业解释」与「购买决策」两端诉求。", "", "2）市场规模与商业化空间", "· 淘宝美妆护肤为高复购、高客单品类；「工具型服务」可提升停留、互动与转化，适配旗舰店与会员运营。", "· 测肤完成后可沉淀历史报告，支撑复购提醒、换季护理与活动召回，形成服务型资产而非一次性流量。", "", "3）需求原声（典型）", "· 「不知道自己适不适合这款抗老精华」　· 「想先测一下再买，别乱试」　· 「报告要能看懂，最好直接告诉我买什么」", ], size=14, color=MUTED, gap=6) # ---- 5 Solution overview ---- s = blank(prs) section_title(s, "02", "小程序方案及价值") add_paras(s, Emu(914400), Emu(1300000), Emu(22000000), Emu(4000000), [ "1）产品价值与商业价值", "· 产品价值：3 步拍摄即可完成 AI 检测，获得综合评分、展示肌龄、七项分析、护理建议与精华推荐。", "· 商业价值：把「不确定」变成「可解释的购买理由」，提升详情页/店铺转化与客单匹配度；报告可复访，利于会员沉淀。", "", "2）商家运用场景与适用行业", "· 适用行业：护肤 / 抗老精华 / 功效型美妆、医美周边护理（非诊疗）、品牌会员中心。", "· 运用场景：店铺首页入口、商品详情页挂载、直播间互动测肤、会员日/换季活动、新客教育与老客复购。", ], size=14, color=MUTED, gap=6) # three value cards at bottom vals = [ ("降低决策成本", "用检测数据替代主观猜测，减少试错与退货。"), ("提升转化效率", "报告页直达适配商品，缩短浏览—下单路径。"), ("沉淀服务资产", "历史报告可回看，支撑持续运营与复购。"), ] for i, (t, d) in enumerate(vals): left = Emu(914400 + i * 7500000) top = Emu(8200000) add_card(s, left, top, Emu(7000000), Emu(3800000)) add_text(s, left + Emu(350000), top + Emu(450000), Emu(6200000), Emu(600000), t, size=16, bold=True, color=ACCENT) add_text(s, left + Emu(350000), top + Emu(1300000), Emu(6200000), Emu(2000000), d, size=14, color=MUTED) # ---- 6 Core features ---- s = blank(prs) section_title(s, "02", "产品核心功能") feats = [ ("授权登录", "淘宝账号授权登录，协议确认后进入服务；账号与报告隔离存储。"), ("基础档案", "出生年月、地区、肤质等信息一次填写、本地缓存，用于个性化展示。"), ("三步拍摄", "正脸 / 右脸 / 左脸手动拍摄或相册选图，压缩后上传检测。"), ("AI 检测报告", "综合评分、肌龄、三维度（紧塑力 / 透亮感 / 稳韧力）与七项分项结论。"), ("护理与推荐", "护理关注点选三、精华产品按肌龄分档推荐，并可跳转店铺商品。"), ("历史报告", "保留本人最近多份完整报告，支持复访对比与复购触达。"), ] for i, (t, d) in enumerate(feats): col = i % 3 row = i // 3 left = Emu(914400 + col * 7500000) top = Emu(1400000 + row * 5200000) add_card(s, left, top, Emu(7000000), Emu(4600000)) add_text(s, left + Emu(350000), top + Emu(450000), Emu(6200000), Emu(700000), t, size=17, bold=True, color=ACCENT) add_text(s, left + Emu(350000), top + Emu(1400000), Emu(6200000), Emu(2800000), d, size=14, color=MUTED) # ---- 7 Product flow ---- s = blank(prs) section_title(s, "02", "产品核心链路") add_text(s, Emu(914400), Emu(1200000), Emu(22000000), Emu(400000), "用户从进入到购买的主路径（交互链路）", size=15, color=MUTED) steps = [ ("1", "启动页", "协议同意\n淘宝授权"), ("2", "基础档案", "年龄地区\n肤质选择"), ("3", "拍摄检测", "正/右/左脸\n上传分析"), ("4", "肌肤报告", "评分肌龄\n七项结论"), ("5", "护理推荐", "关注选三\n精华匹配"), ("6", "商品转化", "跳转详情\n完成下单"), ] for i, (n, t, d) in enumerate(steps): left = Emu(600000 + i * 3900000) top = Emu(2200000) circle = s.shapes.add_shape(MSO_SHAPE.OVAL, left + Emu(1100000), top, Emu(900000), Emu(900000)) circle.fill.solid() circle.fill.fore_color.rgb = ACCENT circle.line.fill.background() add_text(s, left + Emu(1100000), top + Emu(220000), Emu(900000), Emu(500000), n, size=22, bold=True, color=BG, align=PP_ALIGN.CENTER) add_text(s, left, top + Emu(1200000), Emu(3200000), Emu(500000), t, size=16, bold=True, color=TITLE, align=PP_ALIGN.CENTER) add_text(s, left, top + Emu(1800000), Emu(3200000), Emu(1200000), d, size=13, color=MUTED, align=PP_ALIGN.CENTER) if i < len(steps) - 1: add_text(s, left + Emu(3000000), top + Emu(250000), Emu(800000), Emu(500000), "→", size=22, bold=True, color=ACCENT, align=PP_ALIGN.CENTER) add_card(s, Emu(914400), Emu(6200000), Emu(22500000), Emu(5800000)) add_paras(s, Emu(1300000), Emu(6600000), Emu(21000000), Emu(5000000), [ "七项分析：轮廓紧致 · 皱纹细纹 · 肤色色素 · 平滑细腻 · 水分水润 · 敏感泛红 · 痘痘皮损", "三维度评分：紧塑力 / 透亮感 / 稳韧力，支撑综合结论与商品分档推荐", "推荐逻辑：以展示肌龄为主，结合维度评分在边界档位微调，匹配 25+ / 35+ / 50+ 精华组别", "权限说明：拍摄需相机权限；拒绝后可走相册选图；相册权限独立申请，不循环弹窗", ], size=14, color=MUTED, gap=12) # ---- 8 Differentiation ---- s = blank(prs) section_title(s, "02", "与平台现有能力的差异 / 互补") rows = [ ("对比点", "平台现有货架 / 内容能力", "本小程序互补价值"), ("决策依据", "以图文、评价、直播讲解为主", "以本人面部检测数据生成可解释报告"), ("选品方式", "用户自行对比商品参数", "按肌龄与肤质状态主动匹配商品"), ("服务形态", "一次性浏览与成交", "可保存历史报告，支撑复访与复购"), ("商家侧价值", "流量与成交工具丰富", "增加「专业测肤服务」入口，提升信任与转化"), ] for r, row in enumerate(rows): top = Emu(1400000 + r * 1800000) for c, cell in enumerate(row): left = Emu(914400 + c * 7500000) w = Emu(7000000) add_card(s, left, top, w, Emu(1550000)) color = ACCENT if r == 0 or c == 0 else MUTED bold = r == 0 or c == 0 add_text(s, left + Emu(250000), top + Emu(400000), Emu(6500000), Emu(900000), cell, size=13, bold=bold, color=color) # ---- 9 Commercial plan ---- s = blank(prs) section_title(s, "03", "商业化运营规划及目标") add_paras(s, Emu(914400), Emu(1300000), Emu(22000000), Emu(5000000), [ "1）目标覆盖", "· 首期：服务本品牌淘宝旗舰店及核心护肤线（自研自用），完成测肤—推荐—购买闭环验证。", "· 扩展：在验证转化与体验后，可按品牌矩阵店铺复制，或作为会员中心标准服务能力输出。", "", "2）上线后运营策略与节奏", ], size=14, color=MUTED, gap=6) phases = [ ("上线期（0–1 月）", "店铺首页 / 详情页入口曝光；引导完成首测；监控拍摄成功率、报告完成率、推荐点击率。"), ("成长期（1–3 月）", "结合大促与直播挂载测肤；会员专属复测提醒；优化推荐商品与话术转化。"), ("沉淀期（3 月+）", "历史报告召回；换季护理活动；A/B 测推荐规则；持续提升复测率与连带购买。"), ] for i, (t, d) in enumerate(phases): left = Emu(914400 + i * 7500000) top = Emu(6200000) add_card(s, left, top, Emu(7000000), Emu(5800000)) add_text(s, left + Emu(350000), top + Emu(400000), Emu(6200000), Emu(900000), t, size=15, bold=True, color=ACCENT) add_text(s, left + Emu(350000), top + Emu(1500000), Emu(6200000), Emu(3800000), d, size=13, color=MUTED) # ---- 10 KPI ---- s = blank(prs) section_title(s, "03", "关键指标与合规说明") kpis = [ ("体验指标", "拍摄完成率、检测成功率、报告打开时长、历史回访率"), ("转化指标", "推荐位点击率、商品详情跳转率、测肤后下单转化、客单价"), ("运营指标", "日活测肤次数、复测间隔、会员渗透、活动期增量"), ("合规要点", "明示检测用途；相机/相册按需授权；人脸与报告按账号隔离；不做医疗诊断承诺"), ] for i, (t, d) in enumerate(kpis): col = i % 2 row = i // 2 left = Emu(914400 + col * 11000000) top = Emu(1400000 + row * 5200000) add_card(s, left, top, Emu(10000000), Emu(4600000)) add_text(s, left + Emu(400000), top + Emu(500000), Emu(9000000), Emu(700000), t, size=18, bold=True, color=ACCENT) add_text(s, left + Emu(400000), top + Emu(1500000), Emu(9000000), Emu(2600000), d, size=15, color=MUTED) # ---- 11 Thank you ---- s = blank(prs) add_bg(s) panel = s.shapes.add_shape(MSO_SHAPE.RECTANGLE, 0, 0, Emu(3200400), H) panel.fill.solid() panel.fill.fore_color.rgb = PANEL panel.line.fill.background() add_bar(s, Emu(4000500), Emu(5200000), Emu(914400), Emu(90000)) add_text(s, Emu(4000500), Emu(5500000), Emu(16000000), Emu(900000), "THANK YOU", size=44, bold=True, color=TITLE) add_text(s, Emu(4000500), Emu(6500000), Emu(16000000), Emu(500000), "AI 智能测肤 · 淘宝小程序产品方案", size=16, color=MUTED) prs.save(OUT) print("saved", OUT, "slides", len(prs.slides)) if __name__ == "__main__": build()