Koogle d*EPiC SWYNme BITLYme EmailMarketingTipps


discussion Google Postmaster bad IP reputation

There are widespread reports this morning (9/11/17) that Google postmaster tools is showing bad IP reputation for IPs starting on 9/9. This issue is affecting just about everyone. Looking through my client’s postmaster pages, I’m seeing red for IP reputation on every client. Even my clients with generally good reputation are seeing bad reputation since 9/9. [...] [more]
wordtothewise.com    Intelligence, Deliverability

discussion Exploring the Subject Line Series: Non-linguistic approach

oday’s article picks up on email open rate prediction. Which emails do you open? What influences your decision? Is it the subject line? Is it the timing? Is it a lot more? I’m setting out on a quest to discover what influences open rate prediction. I will be sharing what this road map brings back with you. I’d love to hear your comments, love to reply to questions, love to help out. I’m the outgoing type of data scientist, yes. [...] [more]
medium.com    Subjectline, Intelligence

tactics Female, Male, or Neutral? Filtering Based on Gender

Our gender-match filter requires that we first tag users, with our best guess at their gender preference, and items, with our best guess at their gender-specificity. [more]
retentionscience.com    Intelligence, Segmentation

discussion Are You Sending Price Drop, New Arrivals, and Back in Stock Emails to The Wrong Customers?

If you’re sending out a discount email, you want to find the most efficient way to group users who all have a high affinity to a specific item. Here at ReSci, we call it predictive product segments. What this means is that our proprietary AI models are baked into our lifecycle stages. Predictive product segments are an inherent function of our Price Drop, New Arrivals, and Items Back in Stock. Target excess inventory to interested buyers. Retailers may run into an issue with excess inventory due to [...] [more]
retentionscience.com    Intelligence, Segmentation

discussion Simple KPIs in Email Marketing

This is a first of a multipart series in Marketing to list out basic/advance performance indicators, to help improve your marketing. Cutting straight to the chase, here is the user flow when an email sent: [...] [more]
medium.com    Intelligence

discussion 5 Applications For AI In Email Marketing

I’ve been involved in what is now called machine learning since the late 1980s. Compared to the state of the art then, the capabilities of today’s machine learning platform and techniques are breathtaking. A combination of new approaches and cheaper computing power makes what was once considered science fiction into fact (can you say “Hello, [...] [more]
returnpath.com    Intelligence, Trend

tactics So lässt sich Kaufverhalten vorhersagen

Daten lassen vorhersagen, wer sein Zeitungsabo kündigen oder seinen Versicherer wechseln wird. Die Supermarktkette Target erkennt am Surfverhalten weiblicher Kunden ob sie schwanger sind. Lebensversicherungen wollen herausgefunden haben, dass Frührentner auch früher sterben, und Airlines wissen, dass Veganer seltener ihre Maschine verpassen. [...] [more]
email-marketing-forum.de    Intelligence

tactics Email Category Prediction

Email category prediction can be seen as a multi-class classification task, since emails with similar themes may be automatically created using similar templates. The purpose of this paper is to predict a future email to be received by a user according to his previous emails. That is, if a user received a email with certain themes, several days later an email with the same or related templates may be sent to him. [...] [more]
medium.com    Intelligence

discussion Jefferies gives IBM Watson a Wall Street reality check

It seems perfectly reasonable that IBM shot out of the gates like a rocket in a mostly sterile AI market selling to CTOs and newly minted chief data officers with just enough anxiety to open check books. But the reality is that AI isn’t an amorphous black hole that sucks in unstructured data to produce insights. A solid data pipeline and a domain-specific understanding of the AI business problem at hand is table minimum. Coasting on early success won’t cut it in today’s AI-first world where machine [...] [more]
techcrunch.com    ESP, Intelligence, Trend

discussion Machine vs. Marketer — Who Reigns Supreme?

Here’s how it worked: Using their phones, attendees were presented with one of 204 Unbounce-built landing pages. Analyzing only the copy, the AI technology predicted whether the page had an above or below average conversion rate, as benchmarked against thousands of landing pages built in Unbounce. Participants analyzed the pages at the same time and were asked to make their own predictions. Not even the expert marketers were able to beat “The Machine”. [...] [more]
unbounce.com    Intelligence, Conversionrate

tactics How to Use the Lifetime Value Feature in Google Analytics

You’ve got enough KPIs to track and report on already. Why would you possibly need another one? What good would come of adding yet another hour to the end of you’re already long work day in order to dig it up? The truth, in this case, is that you can’t afford not to. Lifetime Value isn’t just another vanity metric. It’s THE metric. The one that stands head and shoulders above all others. IF there was one and only one metric you were tracking, this should be it. And now you can do it simply and easily [...] [more]
kissmetrics.com    Intelligence, Webanalytics

tactics Abmeldungen verhindern, bevor sie passieren

Newsletter-Abmeldungen werden sich wohl nie zu 100 Prozent verhindern lassen. Aber wäre es nicht schön, gefährdete Personen zu identifizieren, noch bevor sie sich tatsächlich abgemeldet haben? Immerhin hätten wir so zumindest die Möglichkeit diese Zielgruppe mit einer besonderen Promo und individuellen Marketing-Inhalten zu überzeugen oder durch Anpassung der Kommunikationsfrequenz eine drohende Abmeldung abzuwehren. [...] [more]
email-marketing-forum.de    Unsubscribe, Intelligence

discussion Break through the hype - uncover the reality of AI [PDF]

A growing number of commerce marketing software providers claim their systems use AI. But it can be difficult to know for sure what that means for your brand and how you can use it to market products and services more effectively to consumers. Does the rise of AI and related technologies signal a sea change in commerce marketing? In a word, yes. [...] [more] 
bronto.com    Intelligence

tactics Behind the Data Science: Sending Item Alerts to the Right Users

Recommendation algorithms usually try to optimize the best set of items (products) to show a specific user. In certain situations it is necessary to obtain the best set of users that might be interested in a specific item. Many digital marketers face the hard problem of targeting the right users not only for their promotional emails, but also for specific item triggers. [...] [more]
retentionscience.com    Intelligence, Recommendation

tactics Design and Models for a Personalized Product Recommendations Engine

Before discussing specific models, it’s important to know a bit about how we store and serve product data for the Bronto Marketing Platform. Our product service uses Solr to support efficient, scalable searches on products based on arbitrary product fields, and it stores data in Apache HBase as a master storage database. The product service already uses Solr to allow customers to search for products (either in the Bronto Marketing Platform user interface or in the Recommendations Standard app), so [...] [more]
bronto.com    Intelligence, Recommendation
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