Different ways to drive value from small data: Thursday’s daily brief

Different ways to drive value from small data: Thursday’s daily brief

If you are a marketer, not a developer (and I’m sure some are), your programming skills are probably very low. Maybe some HTML here and there? Does this mean that low code tools can make your life easier? Do you use it to create customer journeys or campaigns, or to create emails or other content?

Or you use real tools without code to do parts of your work. Maybe a WYSIWYG CMS interface or drag and drop project management tools?

How small businesses can add value with small data

Big data is so evident nowadays that we hardly use the term anymore. But small businesses, many of which, of course, have fewer customers and fewer customer data. Does it have anything to do with the small details?

Some use cases are known: A / B testing does not require big data, just like Net Promoter Scores. Are there ways to generate large amounts of data from smaller data sets? In fact, there are at least two approaches. Some providers, such as Mail chimp, the marketing automation platform, and email marketing, create large data sets for smaller customers. It has artificial intelligence tools that can generate insights from this aggregated and anonymous data.

Proof Analytics takes a completely different approach, using small amounts of data to monitor sales and marketing results in real-time and suggest optimizations, a kind of “business GPS” as the solution calls it. The larger the data set, the less vulnerable to unexpected and unusual events. But, after COVID-19, we can agree that the past is not always a precursor and that real-time analysis applied to smaller data streams offers better response options.

How small businesses can add value with small data

In the world of big data, gigabytes are worth less than a penny. But the change can translate into dollars for a small business. These small digital online stores face the same analytical challenge as their main competitors: finding out who the best customers are and how to sell them.

Small businesses simply don’t have the amount of data – or the resources – to just use big data techniques. But they can always look for a solution that adds value to small data. The methods vary.

Creation of big data from small data

Mail chimp is known for selling email marketing solutions to both small businesses and the big data segment. The company has its own group of data scientists, computer scientists, and mathematicians, explains, director of data at Mail chimp. “The goal is to bottle and put it in the product … You can fill it without using the person”.

On the back, Mail chimp has petabytes of customer data, anonymous to protect your privacy, but available for analysis. Mail chimp uses its machine learning model as an input to the customer’s small business model. Importing big data serves the purpose and keeps the small business model on track,  Small businesses can compare their performance with the averages defined by Mail chimp’s customer base to see how they are rated. These standards can also reveal areas where improvements can be made and best practices that can be used to increase online sales.

In essence, Mailchimp wants small businesses to take advantage of big data-based machine learning by collecting the little data available.

Use small data, like “business GPS”

Another approach is to access and recalculate the data flow in real-time to shape the corporate image, explains the president and CEO of Proof Analytics. ‘It is not difficult to use the data to collect it. It provides observations and increases confidence in the results ”.

For business leaders, a confidence level of about 50, 60, or 70 percent is sufficient, says Stouse. “There is a trend of extreme precision in information technology. Ninety-five percent is the benchmark. He said that under no circumstances can the business user gain 95% confidence,

Since small data can be recalculated in real-time, they are comparable to GPS. “It allows you to fix the problem and make changes,” as well as changing the route during the trip, said Stouse.

Some crazy about the family

Working with small data must be very familiar. There are always little data, even if you don’t use a platform or service to analyze it. “It’s less about the algorithm,” says Scott Brinker, VP, HubSpot Platform Ecosystem. “It’s more about the content. How much of the content is good?”

Big data algorithms can classify millions of process changes to predict the best message to deliver the best response to a group of customers. ‘The black box is too much. You lose the plot

If he has a clear idea of who the customer is, he can guide him better: a small data model in marketing thinking instead of a big data algorithm, he explained. Small data techniques are common, varied, and have been around for some time.

The Net Promoter Score (NPS) simply collects feedback from these pop-ups for small customer surveys and asks the user to rate a service or product on a scale of 1 to 10.9 and 10 as promoters. Less than six is offensive. However, this type of data can only display hundreds or thousands of responses, Brinker noted. “I’m definitely not big data.”

The EU can force key engineers to pay for news links

Following in Australia’s footsteps, European lawmakers could force technology companies to pay for the news. According to the Financial Times, predetermined regulations are subject to change and contain provisions related to changes in Australia.

George Nguyen, the editor of Search Engine Land, writes: “ It is unreasonable to expect Google to pay to link publishers to the best results … If Google is forced to pay news organizations for … other sectors, Google will also pay