Optimizing Digital Marketing Campaigns for Furniture Retailers: Keyword Strategy and Ad Design Using ML

by Shivam Kashyap

The goal of this project is to improve the effectiveness of an online furniture retailer’s digital marketing through the development of a successful seeded keyword list and attention-catching ad visuals. It remains the duty of our proposed SEO and PPC strategies to increase the online presence and conversion of the retailer by focusing on certain product segments, customers’ preferences.

Our methodology includes:

  1. Keyword Generation: Some of the prices sensitive and promotional words related to furniture products like sofa, recliner, and sofa bed, and so on.
  2. Ad Grouping: Creating the specific ad groups based on keywords strictly interconnected that guarantee the maximum target ability and relevance.
  3. Ad Design: Developing effective headlines for the ads that match the potential keywords and the audience, stressing the low price and special offers on the landing pages.
  4. Data Analysis: Measuring the impact and success of the campaigns inform of CTR, Conversion Rates and email open rate and making improvements on the strategy.

That is why, the results show that an accurate KW choice and adequately developed individualized ad designs affect the effectiveness of digital promotion to a great extent. Thus, prioritising the use of accurate and specific keywords, we improve the relevance of the ads and guarantee the better places of the ads’ placement. This in turn leads to more visits on the website and increase in the conversion rate.

Thus, the findings of the current research have practical implications for digital marketers designing effective campaigns for sensitive price consumers. The study also concerns the

importance of further control to improve the company’s performance as a dynamic environment requires constant changes. Furthermore, it adds to the existing body of knowledge regarding the efficiency of the digital marketing approaches in the case of online retailing.

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