What is Customer Data?
Customer data can uncover essential information that restaurant professionals can utilize to create better management and marketing decisions. Bloom Intelligence can expose daily foot traffic, first-time visitors, average dwell time, popular visit times, dwell time by hour, first-time visitor return rates, average customer repeat rates, gender distribution, and much more.
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What is Marketing Data?
Marketing should only begin after acquiring customer data. A successful marketing campaign requires a thorough understanding of customer bases, behavior, activity, and opportunities. Examples of marketing data built into Bloom Intelligence’s all-in-one platform includes email opens, emails delivered, emails bounced (not successfully delivered), clicks within emails, clicks within WiFi landing pages, unsubscribes, and more. WiFi landing pages can uncover this data and can trigger automated personalized campaigns based on age, gender, zip code, and more.
Why Collect Data?
Let’s face it. Customers have almost unending dining choices.
For food and beverage professionals, it’s critical to:
- Stand out against the competition.
- Create a data-driven management plan.
- Acquire new customers.
- Increase customer loyalty.
- Understand who customers are and what they like.
In the past year, many restaurants have learned that the digital era is here to stay. More importantly, evolution is no longer a choice. It is a necessity.
However, today there are unending data acquisition choices available for restaurants. It’s imperative to cut through the red tape to cut costs and find an all-in-one data acquisition, management, and marketing solution.
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Step One: Analyze
Data tells a story. When analyzing data, interpreting the story behind the numbers is critical. For example, when traffic is down one day and increases the next, it could be due to outside traffic from a local event versus a marketing campaign.
Step Two: Understanding
After analyzing data, understanding why these data points exist is essential. For example, maybe customer reviews have increased after running an automated feedback loop campaign.
Step Three: Evaluate
Evaluate possible improvements. For example, if customer reviews have increased after running an automated feedback loop campaign in one location, it might make sense to activate the campaign in other locations, as well.
Step Four: Apply
When applying data campaigns or organizational improvements, it’s essential to continue to track these data. What performs well in one location might fail in other places. Frequently find ways to use data and improve results.
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Data acquisition is the process of obtaining data from a variety of sources. Interpreting these data is possibly the most critical component of data acquisition.
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