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That class can instantly parse your input string with out bothering to outline a formatting pattern. The DateTime sort has a .Date property which returns the DateTime with the time value set as above. This seems just like the number of seconds / milliseconds from some epoch. If you know the epoch you possibly can create the date by including on the right amount of time. Notice the timezone offset included as a part of the worth. This resolution got my object from the callback method and displayed the dates on the web page correctly using the date format library.

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Since you’ll find a way to’t cross datetime format to astype(), it is somewhat primitive and it’s better to make use of pd.to_datetime() instead. I am starting to suppose that that sadly has restricted application and you’ll have to use various different methods of casting the column varieties eventually, over many lines. I tested ‘class’ and that labored, so it will take things which are actual python types like int or complex and then pandas terms in citation marks like ‘class’. If you guys are on the lookout for an answer for Android, you ought to use the following code to get the epoch seconds from the timestamp string. The Joda-Time project, now in upkeep mode, advises migration to the java.time courses.

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However, if the browser executes this in the identical timezone as the server that generated it does not matter and most of the answers work. I discovered the reply here useful, but a slight edit to the regex is required, as it appears that the timezone GMT offset is being appended onto the quantity returned (since 1970) in WCF JSON. If you want to convert multiple columns into datetime64 (which is commonly the explanation astype() is used), then you possibly can apply pd.to_datetime(). It does this by making an implicit call to TO_CHAR() (or some other inner method of stringifying dates) and uses a default format masks to perform this conversion. The Instant class represents a moment on the timeline in UTC with a decision of nanoseconds.

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The old date-time lessons bundled with the earliest variations of Java have proven to be poorly designed, confusing, and troublesome. By clicking “Post Your Answer”, you agree to our phrases of service and acknowledge you’ve read our privacy coverage. There is explained on final assist page that %DATE% expands to the present locale date and %TIME% to the current locale time on parsing the line containing those dynamic variable references. Connect and share data inside a single location that is structured and straightforward to look. To insert the current date you’ll find a way to just use this GETDATE() operate. Considering there is solely one column within the table…You can regulate the insertion values based on your desk.

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As you probably can guess, this means that you have all the attendant timezone issues round it, despite the very fact that for a Date object you’d want absolutely no timezone handling. Dates are often represented as a DateTime object with the time set to midnight. Unfortunately you have to swap to the older eval route so as to get Dates to parse globally in-place – otherwise you need to convert them on a extra case-by-case foundation post-parse. In jQuery 1.5 you can avoid overriding the parseJSON method globally by utilizing the converters choice within the Ajax call. We first detect what type of date we’re consuming, parse it into a normal JavaScript Date object, then format that out. If you don’t need to repeat your date conversion code again and again I counsel you read this weblog submit and get the code that can make your life slightly simpler.

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The right facet of the SET command, in your case, is setting a Filename (for later use somewhere) into the current environment variables. Sadly I misunderstood the question and thought you have been asking about SET quite than what was being set.You can take a look at your SET commands by typing SET (with no paremeters) in your command immediate. I created a simple Date struct for occasions whenever you want a simple date with out worrying about time portion, timezones, local vs. utc, etc. In different words, the intention here is that the time portion is meaningless.

• The Instant class represents a moment on the timeline in UTC with a resolution of nanoseconds.
• If you aren’t involved in regards to the time portion, then you can also use the ANSI Date literal which uses a hard and fast format ‘YYYY-MM-DD’ and is NLS unbiased.
• Visit one of our retailer areas to enjoy the full Costa Coffee expertise.
• This format is outlined by the wise sensible normal, ISO 8601.
• I actually have this a half of script that create a variable referred to as fileName used later to call a file.

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Again, for the sake of completeness, I’ve written a solution to parse this Date-Time string using the Joda Date-Time API. Note that from Java SE eight onwards, users are asked emigrate to java.time (JSR-310) – a core a part of the JDK which replaces this project. Do not use ‘Z’ in the sample with the Date-Time parsing/formatting API. For the sake of completeness, I’ve written a solution to parse this Date-Time string using the legacy API.

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Visit one of our store locations to benefit from the full Costa Coffee expertise. It took 112 attempts to develop our well-known signature blend, slow-roasted with the best sustainably sourced beans. By sluggish roasting our beans we’re sweetening any bitterness in life by means of making a great tasting coffee, from the very first sip. With that being stated, when you dump it into a database (such as sqlite), an object dtype column of datetime.date objects saved as a DATE sort (whereas datetime64[ns] will be saved as TIMESTAMP). If you aren’t involved in regards to the time portion, then you could additionally use the ANSI Date literal which makes use of a set format ‘YYYY-MM-DD’ and is NLS impartial. This does not keep in mind WCF format with timezone offsets, although that may be comparatively simple to add.

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As JSON has a unfastened DateTime implementation, you have to use the IsoDateTimeConverter(). Note that since Json.NET 4.5 the default date format is ISO so the code below is not needed. The substr() operate takes out the /Date( part, and the parseInt() function gets the integer and ignores the )/ on the end. The ensuing quantity is passed into the Date constructor. I had a look at this answer about casting date columns but none of them seem to suit into the elegant syntax above. SQL/Plus and SQL Developer will use the user’s session parameter NLS_DATE_FORMAT to perform this conversion – see this reply relating to this.

I am working on a program that requires the date of an event to get returned. The original asker was most likely in EST and had a pure date (sql) or a DateTime (not DateTimeOffset) with midnight. Another bonus to doing it this manner is that you can simply (and efficiently) select all information for a given yr or month by leveraging the means in which CouchDB handles queries on array values. Just considering exterior the field right here — a JSON date doesn’t have to be saved as a string. From somebody completely new to JSON – How do I format this to a short date format? I’ve tried the jQuery.UI.datepicker plugin using $.datepicker.formatDate() with none success.

• As you presumably can guess, because of this you’ve all the attendant timezone issues around it, despite the very fact that for a Date object you’d want completely no timezone handling.
• As JSON has a unfastened DateTime implementation, you should use the IsoDateTimeConverter().
• The Z on the top means UTC (that is, an offset-from-UTC of zero hours-minutes-seconds).
• Unfortunately you have to change to the older eval route in order to get Dates to parse globally in-place – otherwise you need to convert them on a extra case-by-case foundation post-parse.
• This creates an setting variable called FRIEDRICE and units the value to YES.

It’s barely extra keen and grabs everything between the parens, not simply the primary quantity. The ensuing time sinze 1970, plus timezone offset can all be fed into the eval to get a date object. The java.time courses use ISO 8601 by default when parsing/generating textual representations of date-time values.

Even with read_csv, you have some control over the format, e.g. The Z at the end of the Pattern must be wrapped in ‘Z’ identical to the ‘T’ is. Change”yyyyMMdd’T’HHmmss.SSSZ” to “yyyyMMdd’T’HHmmss.SSS’Z'” and it works. This technique interprets java.util.Date to UTC format (or any other) and back again.

Instead, use the java.time framework constructed into Java eight and later. The java.time lessons supplant each the old date-time lessons and the extremely profitable Joda-Time library. Like we have done for decades, pass a numeric offset from the de-facto commonplace epoch of 1 Jan 1970 midnight GMT/UTC/&c in variety of seconds (or milliseconds) since this epoch. JavaScript likes it, Java likes it, C likes it, and the Internet likes it. I included logic that assumes you send all dates from the server as UTC (which you should); the buyer then will get a JavaScript Date object that has the right ticks value to replicate this. I also had to seek for an answer to this drawback and ultimately I came throughout moment.js which is a pleasant library that can parse this date format and plenty of extra.

I used it for getting off the bottom, however I do not use this any extra. However, I nonetheless feel the best reply lies with altering how the server formats https://mybride.net/costa-rican-brides/ the date, for example, ISO as mentioned elsewhere. Just after retrieving the JSON I go fixup the dates to be JavaSript Date objects using the Date constructor which accepts an ISO 8601 date string…

In the evolving landscape of digital marketing, simply segmenting audiences by broad demographics no longer suffices. To truly resonate with niche audiences, marketers must implement hyper-specific, data-driven micro-targeted messaging strategies. This article delves into the technical, tactical, and strategic nuances necessary to craft, execute, and optimize these campaigns, transforming your approach from generic to highly personalized communication. For broader context, explore our comprehensive guide on «How to Implement Micro-Targeted Messaging for Niche Audiences». Later, we connect these tactics to foundational marketing principles in «Understanding Audience Segmentation and Personalization». Let’s begin by precisely defining and segmenting your niche audiences with expert-level rigor.

1. Identifying and Segmenting Niche Audiences for Micro-Targeted Messaging

a) Step-by-step process to define hyper-specific audience segments using demographic, psychographic, and behavioral data

Achieving precise segmentation begins with a systematic approach that combines multiple data dimensions. Start by collecting comprehensive demographic data: age, gender, income, education, and geographic location. Next, enrich your dataset with psychographic insights—values, lifestyles, interests, and personality traits—via surveys, social media profiling, or third-party psychographic tools like Claritas or YouGov. Finally, incorporate behavioral data such as purchase history, website interactions, email engagement, and social media activity. Use a hierarchical segmentation framework to identify micro-segments:

• Layer 1: Broad segments based on demographics (e.g., urban eco-conscious professionals aged 30-45)
• Layer 2: Sub-segments refined by psychographics (e.g., environmentally motivated urban professionals interested in sustainable living)
• Layer 3: Behavioral clusters (e.g., frequent buyers of eco-friendly products, active on sustainability forums)

This layered approach ensures your micro-segments are both narrowly defined and actionable, enabling tailored messaging that addresses specific needs and motivations.

b) Tools and techniques for gathering granular audience insights, including advanced analytics and social media listening

Leverage advanced analytics platforms such as Google Analytics 4, Mixpanel, or Heap to extract behavioral patterns. Integrate these with CRM systems like Salesforce or HubSpot to correlate offline and online data. For psychographic insights, utilize social media listening tools like Brandwatch, Sprout Social, or Talkwalker to monitor conversations, sentiment, and trending topics within your niche. Use natural language processing (NLP) algorithms to identify nuanced preferences and pain points expressed by your audience. Additionally, employ cluster analysis and predictive modeling techniques—via Python or R—to uncover hidden segments and forecast future behaviors, enabling you to craft highly relevant messages.

c) Case study: How a local business refined its niche segments to improve engagement rates

A boutique coffee shop in Portland wanted to increase local engagement. They started by analyzing POS data to identify high-frequency customers interested in specialty brews. Social listening revealed eco-conscious urban professionals actively discussing sustainable lifestyles. Combining these insights, they segmented their audience into micro-groups such as “Eco-conscious coffee enthusiasts aged 25-40 in NW Portland.” They then tailored messages highlighting their organic, locally sourced beans, and sustainability initiatives. Implementing targeted Facebook and Instagram ads with dynamic creative based on these segments increased their engagement rate by 35% within three months, demonstrating the power of precise segmentation.

2. Crafting Precise and Resonant Messaging for Micro-Segments

a) Developing tailored value propositions that address unique audience pain points and preferences

To craft compelling value propositions, start with deep audience empathy. Conduct qualitative interviews or focus groups with a representative micro-segment to understand their specific challenges and aspirations. Map these insights to your product or service benefits, emphasizing solutions that resonate on a personal level. For example, for eco-conscious urban professionals, a value proposition like “Sustainable coffee that energizes your mornings while supporting local farmers” directly addresses their environmental values and daily needs. Use frameworks like the Jobs-to-Be-Done methodology to articulate exactly what your audience seeks to accomplish, ensuring your messaging hits core motivations.

b) Techniques for personalization: leveraging dynamic content and conditional messaging rules

Implement personalization by deploying dynamic content blocks within your email marketing platforms like HubSpot, Marketo, or Salesforce Pardot. Use conditional logic based on audience attributes—such as location, behavior, or psychographics—to serve tailored messages. For example, a micro-segment of urban eco-enthusiasts might see an email highlighting your new organic blend and your commitment to sustainability, while another segment receives a message emphasizing your local sourcing partnerships. Set up rules like:

Condition	Content Variation
Location = NW Portland	Highlight local sourcing stories
Interest = Sustainability	Emphasize eco-friendly practices

This approach ensures every recipient perceives a personalized, relevant message, significantly increasing engagement.

c) Practical example: Creating personalized email sequences for a micro-segment of eco-conscious urban professionals

Design a sequence that progresses as follows:

1. Initial email: Introduce your brand’s sustainability story, tailored to urban lifestyles, with dynamic content showing local sourcing images if location data is available.
2. Follow-up email: Share customer testimonials from similar micro-segments, emphasizing environmental impact.
3. Conversion offer: Provide a personalized discount or loyalty reward, triggered by previous engagement or browsing behavior.
4. Re-engagement: Send a survey or poll to gather feedback on sustainability initiatives, reinforcing your commitment and capturing insights.

This tailored sequence increases relevance, builds trust, and drives conversions within hyper-specific segments.

3. Technical Implementation of Micro-Targeted Campaigns

a) Setting up audience segmentation in marketing automation platforms (e.g., HubSpot, Marketo)

Begin by creating custom fields or tags for each micro-segment attribute—demographics, psychographics, behaviors. Use these to build static or dynamic lists. In HubSpot, for example, you can set up smart lists with criteria such as “Contact property | Location | equals | NW Portland” AND “Contact property | Interest | contains | Sustainability.” Ensure your data collection forms capture these attributes explicitly, and set up workflows that automatically assign contacts to segments based on their responses or behavior.

b) Configuring conditional logic and dynamic content blocks to serve tailored messages

Within your email or ad platform, implement if-else logic to dynamically change content. For example, in Mailchimp or ActiveCampaign, you can insert conditional blocks like:

{{#if interest_sustainability}}
  
Highlight your eco-friendly sourcing and green initiatives.
{{else}}
  
Focus on quality and flavor details.
{{/if}}

This method ensures each recipient receives a message that aligns precisely with their profile, maximizing relevance and engagement.

c) Integrating third-party data sources for enhanced targeting accuracy

Enhance your segmentation with third-party data providers like Acxiom or Experian to incorporate lifestyle and intent data. Use API integrations to append these attributes to your CRM records. For instance, adding data on consumers’ purchase intent or environmental activism levels enables you to refine segments further. Ensure your data handling complies with privacy regulations, and validate data quality regularly to prevent segmentation drift.

d) Step-by-step guide: Building a segmented campaign flow from initial segmentation to message delivery

Stage	Action
Data Collection	Gather demographic, psychographic, behavioral, and third-party data
Segmentation	Create detailed segments using platform tools and custom attributes
Content Personalization	Design dynamic email templates with conditional blocks
Workflow Automation	Set up triggers, delays, and actions based on segment attributes
Execution & Monitoring	Launch campaign, track KPIs, and adjust parameters dynamically

4. Testing and Optimizing Micro-Targeted Messages

a) Designing A/B tests for individual segments to measure message effectiveness

Create clear hypotheses—for example, testing subject line variations or call-to-action (CTA) phrasing. Use platform tools to split your segment randomly into control and test groups, ensuring sample sizes are statistically significant. Track performance metrics such as open rates, click-through rates, and conversions. Use statistical significance calculators to validate results before implementing winning variations.

b) Metrics to monitor: engagement rates, conversion rates, and audience feedback

Key metrics include:

• Open Rate: Indicates subject line and sender relevance
• Click-Through Rate (CTR): Measures message resonance
• Conversion Rate: Tracks goal completions like purchases or sign-ups
• Unsubscribe Rate: Flags message fatigue or misalignment
• Audience Feedback: Gather qualitative insights via surveys or direct responses

c) Common pitfalls: over-segmentation and message fatigue—how to avoid and correct them

Over-segmentation can lead to overly complex workflows that are difficult to manage and can cause audience fatigue. To prevent this, establish a max segmentation threshold—for example, no more than 10-15 micro-segments. Regularly review engagement metrics to identify segments showing diminishing returns, and consolidate or refresh messaging. Use a rotation calendar to avoid bombarding the same audience repeatedly, and incorporate feedback loops to adapt content based on real-time responses.

d) Example: Iterative refinement of messaging based on real-time performance data

Suppose a segment of urban eco-enthusiasts shows a declining open rate over two campaigns. Use platform analytics to identify which subject lines performed best. Test new variants emphasizing different value propositions—such as sustainability impact vs. product quality. Implement a multivariate test to optimize messaging. Once a winning combination emerges, update your templates and schedule regular reviews to sustain engagement and adapt to evolving preferences.

5. Ensuring Privacy and Ethical Considerations in Micro-Targeting

a) Best practices for compliance with GDPR, CCPA, and other privacy regulations

Implement clear, granular consent mechanisms—use explicit opt-in forms explaining data usage. Maintain a detailed Record of Processing Activities (ROPA) and ensure data minimization by collecting only necessary attributes. Regularly audit your data handling practices, and provide easy options for users to update or withdraw consent. Use privacy-by-design principles when configuring your segmentation and personalization systems.

b) Techniques for transparent data collection and obtaining user consent

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