Why Tools Cannot Solve Broken Product Data
[dnxte_text_highlight highlight_text=”Introduction” stroke_color=”#ffb819″ stroke_width=”8px” dnxt_svg_select=”double-line” _builder_version=”4.27.4″ _module_preset=”default” heading_fonts_font=”–et_global_body_font||||||||” heading_fonts_text_color=”#009BDD” heading_fonts_font_size=”20px” animation_fonts_font=”–et_global_body_font||||||||” animation_fonts_text_color=”#009BDD” animation_fonts_font_size=”24px” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” animation_fonts_font_size_tablet=”24px” animation_fonts_font_size_phone=”20px” animation_fonts_font_size_last_edited=”on|phone” global_colors_info=”{}”][/dnxte_text_highlight]
Many teams invest in new software thinking it will clean up their product data. The reality is different. Search still fails, filters still confuse buyers, and returns keep climbing. The real obstacle is the quality of the data.
This whitepaper explains why disorganized product data blocks growth and how to fix it with the right foundation of taxonomy, enrichment, and governance.
[dnxte_text_highlight highlight_text=”What You’ll Learn” stroke_color=”#ffb819″ stroke_width=”8px” dnxt_svg_select=”double-line” _builder_version=”4.27.4″ _module_preset=”default” heading_fonts_font=”–et_global_body_font||||||||” heading_fonts_text_color=”#009BDD” heading_fonts_font_size=”20px” animation_fonts_font=”–et_global_body_font||||||||” animation_fonts_text_color=”#009BDD” animation_fonts_font_size=”24px” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” animation_fonts_font_size_tablet=”24px” animation_fonts_font_size_phone=”20px” animation_fonts_font_size_last_edited=”on|phone” global_colors_info=”{}”][/dnxte_text_highlight][dnxte_feature_list_parent dnxte_feature_list_icon_color=”#ffb819″ dnxte_feature_list_icon_size=”18px” dnxte_feature_list_item_padding=”|0px|20px||false|false” dnxte_feature_list_title_padding=”|0px|||false|false” dnxte_feature_list_icon_size_tablet=”18px” dnxte_feature_list_icon_size_phone=”14px” dnxte_feature_list_icon_size_last_edited=”on|phone” dnxte_feature_list_item_padding_tablet=”|0px|20px||false|false” dnxte_feature_list_item_padding_phone=”||10px||false|false” dnxte_feature_list_item_padding_last_edited=”on|phone” _builder_version=”4.27.4″ _module_preset=”default” title_font=”–et_global_body_font||||||||” title_text_color=”#445d82″ title_font_size=”18px” max_width=”90%” custom_margin=”10px|-22px|||false|false” title_font_size_tablet=”18px” title_font_size_phone=”14px” title_font_size_last_edited=”on|phone” global_colors_info=”{}”][dnxte_feature_list_child dnxte_feature_list_title=”The definition of product data and why it becomes messy.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”The hidden costs of poor data: lost revenue, higher returns, and wasted time.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”Examples of how weak data breaks search, filters, and product pages.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”Why surface cleaning does not address the root cause.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”How people and automation together can create lasting governance.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”A 30-60-90 day plan to stabilize product data and prove value.” dnxte_feature_list_icon=”||divi||400″ dnxte_feature_list_icon_color=”#ffb819″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][/dnxte_feature_list_parent][dnxte_text_highlight highlight_text=”Why It Matters” stroke_color=”#ffb819″ stroke_width=”8px” dnxt_svg_select=”double-line” _builder_version=”4.27.4″ _module_preset=”default” heading_fonts_font=”–et_global_body_font||||||||” heading_fonts_text_color=”#009BDD” heading_fonts_font_size=”20px” animation_fonts_font=”–et_global_body_font||||||||” animation_fonts_text_color=”#009BDD” animation_fonts_font_size=”24px” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” heading_fonts_font_size_tablet=”20px” heading_fonts_font_size_phone=”18px” heading_fonts_font_size_last_edited=”on|phone” animation_fonts_font_size_tablet=”24px” animation_fonts_font_size_phone=”18px” animation_fonts_font_size_last_edited=”on|phone” global_colors_info=”{}”][/dnxte_text_highlight]
When product data is incomplete or inconsistent, every process slows down. Customers cannot find items, filters show duplicates, and descriptions mislead. Returns increase, onboarding stalls, and sales decline.
Structured, governed product data creates the foundation that lets PIM, MDM, eCommerce, search, and AI deliver consistent results.
[dnxte_feature_list_parent dnxte_feature_list_icon_color=”#ffb819″ dnxte_feature_list_icon_size=”18px” dnxte_feature_list_item_margin=”||||false|false” dnxte_feature_list_item_padding=”||25px||false|false” _builder_version=”4.27.4″ _module_preset=”default” title_text_color=”#ffffff” title_font_size=”20px” title_line_height=”150%” max_width=”70%” module_alignment=”center” custom_margin=”130px||||false|false” custom_padding=”||||false|false” custom_padding_tablet=”||||false|false” custom_padding_phone=”0px||0px||false|false” custom_padding_last_edited=”on|phone” title_font_size_tablet=”20px” title_font_size_phone=”14px” title_font_size_last_edited=”on|phone” global_colors_info=”{}”][dnxte_feature_list_child dnxte_feature_list_title=”Faster onboarding with fewer manual fixes.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”Search and filter results that guide buyers to the right product.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”Fewer returns and higher customer satisfaction.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][dnxte_feature_list_child dnxte_feature_list_title=”Clear ownership and governance that prevent recurring issues.” dnxte_feature_list_icon=”||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][/dnxte_feature_list_child][/dnxte_feature_list_parent]
[dnxte_text_highlight highlight_text=”Download the White Paper” highlight_alignment=”center” stroke_color=”#009BDD” stroke_width=”0px” dnxt_svg_select=”double-line” _builder_version=”4.27.4″ _module_preset=”default” heading_fonts_font=”–et_global_body_font||||||||” heading_fonts_text_color=”#009BDD” heading_fonts_font_size=”34px” animation_fonts_font=”–et_global_body_font||||||||” animation_fonts_text_color=”#009BDD” animation_fonts_font_size=”34px” max_width_tablet=”” max_width_phone=”60%” max_width_last_edited=”on|phone” module_alignment=”center” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” animation_fonts_font_size_tablet=”34px” animation_fonts_font_size_phone=”24px” animation_fonts_font_size_last_edited=”on|phone” global_colors_info=”{}”][/dnxte_text_highlight]
Read The Dirty Data Trap to see how companies are repairing their foundation and using product data to drive measurable results.