Key Analytic Insights to Inform Business Decisions

Mihir Kittur

May 22, 2020

Today’s digital ecosystem provides a rich trove of data. For marketers, simply tracking Traditional Marketing analytic is not enough to stay ahead of the competition. Digital data can be harnessed to produce advanced insights that can be leveraged to improve Marketing effectiveness. There are three types of Digital Intelligence that you should be using to your advantage:

1. Customer Sentiment

Today, customers are quick to post reviews which, in turn, influence future purchase decisions. Customer reviews and feedback are often an under-leveraged resource, especially in the online-first world today. While you may already have an overview of top-level themes emerging from customer reviews, marketers are now seeking deeper insights to differentiate and better compete.

Detailed customer sentiment insights present multiple opportunities for a brand, like:

Next-Generation of Products – If, for example, customers are complaining about faulty handles – the product team can leverage that insight to make product improvements and/or create products in the future that better cater to customers’ needs.

Marketing Messages – Marketers can leverage these insights to create differentiated/unique messages that reflect what customers are saying about the brand.

By blending AI technology with human validation expertise, you can also gain deeper, more accurate insights into customer sentiments at scale. This allows you to analyze customer sentiments across various data sources, such as product reviews on your website, product reviews from competitor websites, and internal sales data.

Leveraging Natural Language Processing (NLP), you can extract keyword phrases from customer reviews, group them into themes, and classify them as positive or negative customer sentiments.

2. Product Content

Businesses must understand that they are not just competing across a category, they are also competing against overall experience. Listing products with incomplete or inaccurate descriptors leads to poor customer experiences. Accurate product content helps to educate buyers to make confident purchase decisions. Marketers can capitalize on these three strategies:

Competitive Content Elements – Insight on how customers search for products or competitor product data can inform what brand content is needed.

Missing Content – Getting timely alerts on products that are missing basic content requirements, such as images, specs, descriptions, etc., can help improve brand representation.

Search Performance – Improving content based on such insights will drive a positive impact on Google page ranks, web traffic, page views, and conversions.

The best place to start is to simply evaluate the listings that you already have in place to identify any gaps. Understanding your KPIs will also help uncover your product page gaps (examples could be share of shelf, share of search, etc.). What products are experiencing low page views or site traffic, or high exit rates? You should also identify whether or not you are missing images, specs, or keywords that would help customers learn more or find you easier? Next, research what keywords should be included for each product.

Lastly, once you’ve enriched your content, you can measure its effectiveness against key parameters such as site traffic, engagement, and conversion. Using Machine Learning, you can also activate and measure improvements for automatic updates over time.

3. Competitive Pricing Analysis

Consumers are constantly examining and comparing their options to ensure that they are getting the best price on the best products. Marketing campaigns can use pricing insights to contribute to improvements in click rate and return on marketing spend at both the macro level and at the customer segment level. Some examples of this are:

Product Promotion – Insights on price competitiveness can help marketers promote brands that have a competitive price advantage.

Product Pricing Personalization – Marketers are leveraging these insights to offer personalized prices by combining customer data and pricing insights.

Adopting a systematic, technology-enabled approach can help curate accurate pricing insights at scale. Begin by monitoring competitive prices on key-value items to gain an objective understanding of your price position. Through rules and price optimization algorithms, identify the right price customers are willing to pay. Ensure the pricing is competitive and maximizes profits or revenue.

Conclusion

Today’s digital ecosystem offers marketers a tremendous opportunity to learn more about their customers and deliver more competitive content and pricing to improve digital performance.