As the eCommerce landscape continues to evolve, online business owners have to adapt to stay relevant in their market. Coupled with high inflation, startups need to raise their prices just high enough to make a good profit without pricing themselves out of their consumers’ reach.
Seems like a difficult task. However, it’s still possible to formulate a data-driven marketing strategy that improves website conversion. All you’ll need is data and analytics software and some free time.
How to Create a Data-Driven eCommerce Strategy
Customer buying behaviors are always changing. Adapting to these changes will be difficult without data and analytics software or the right KPIs.
Here’s how to formulate your a data-driven marketing strategy.
Step 1: Gather and Centralize Data About Current Customers
Your customers are the best sources of information, as they’ve already converted into future buyers. If you already have web analytics software set up or you can view your social media metrics, check which posts, ads, or website pages lead customers through the buyer’s journey.
With the rise in cloud applications, you store your data in more than one location. However, it’s better to centralize your data in a structured system. When your data is in one location, it’s much easier to understand.
If you aren’t using analytics software (or CRM/BI software), research your target audience via market research, competitor analysis, and a centralized data platform. A buyer persona should include a person’s interests, age, gender, purchasing decisions, and relevant subcultures.
Step 2: Adjust Your Strategy With More Relevant Metrics and KPIs
All eCommerce businesses, no matter their niche, should review their marketing strategies regularly to ensure they’re tracking the right metrics and KPIs. You can use specific KPIs to boost marketing performance, but you have to pay attention to what you want to measure.
To determine which KPIs are appropriate for your brand, consider the current growth stage of your brand, how your followers engage with your product, and the platforms your buyers use.
It’s important to note that marketing KPIs are different from general metrics, as KPIs are often made up of multiple marketing metrics. Some fantastic marketing KPIs include Return on Marketing Investment (ROMI), Lead Conversion Rate, and Return on Advertising Spending.
Validate your concepts for performance during the design stage with AI-generated attention analytics
Step 3: Analyze Data for Trends and Patterns (for Each Campaign)
Now that you’ve centralized your data and started to track your new (and relevant) KPIs and metrics, you can start to analyze industry trends. As you’re looking at the data, you’ll notice that your audience is more likely to interact with one product, service, ad, or content over others.
These indicate a buying pattern, but these patterns may not always indicate your audience’s buying behavior. You need to review your data and analytics for at least a month to be sure.
Of course, it’s better to have a large sample size and 6 months of stored data to analyze, as it’ll present the most accurate conclusion. However, eCommerce buying trends change quickly, so use an AI-backed data platform that identifies the most common correlations every single week.
Step 4: Create Separate Campaigns for Different Target Groups
It’s in your best interest to niche down when opening an eCommerce store. Not only does this increase product-market fit, but it also saves you time and money because you’re reducing the number of people you want to sell to. With that said, some general stores can still thrive online.
Even if you target a niche market, there’s still value in separating campaigns into different target groups. Your customers may differ greatly depending on location, so it pays to offer variety.
For example, Lucky Charms recently noticed that adult Millennials with no children make up a large portion of their purchasing demographic. While parents make up the biggest audience, Lucky Charms has to market to these target groups differently if they want to increase sales.
Step 5: Personalize, Coordinate, and Invest in Predictive Analytics
Mass marketing is largely ineffective because it only resonates with a small portion of your audience. However, personalization will be more applicable to each group. If cart abandoners and general email subscribers receive the same messaging, you’ll lose out on more sales.
On the other hand, you should coordinate marketing materials across all channels. Also known as omnichannel marketing, this approach can help you improve the quality of your user data.
Predictive analysis is another great way to improve the quantity and quality of your leads. When you can separate each data group into high vs. low conversion potential, you can target the best traffic groups instead. This solution can benefit from a marketer with high marketing expertise.
Conclusion
Creating a data-driven marketing strategy is much easier thanks to cloud-based data software, but it can only do half of the work. eCommerce businesses must know what KPIs to track, who their audience is, why their buyers shop with them, and how to advertise to them effectively.
