r psm傾向性匹配_南瓜香料指標psm如何規劃季節性廣告

r psm傾向性匹配

Retail managers have been facing an extraordinary time with the COVID-19 pandemic. But the typical plans to prepare for seasonal sales will be a new challenge. More seasonal products have been introduced over the years, making August the best point to conduct a seasonal analysis. So this means you, as a marketer, can get to understand seasonal shopping

零售經理面對COVID-19大流行正處于非同尋常的時期。 但是為季節性銷售做準備的典型計劃將是一個新的挑戰。 多年來引入了更多的季節性產品,使8月成為進行季節性分析的最佳時機。 因此,這意味著您作為營銷人員可以了解季節性購物

I have a nickname for the online metrics associated with seasonal retail behavior. I call them Pumpkin Spice Metrics or PSMs, given that so many products with a pumpkin theme arrive in stores during the fall.

我有一個與季節性零售行為相關聯的在線指標的昵稱。 鑒于秋季有許多以南瓜為主題的產品到貨,因此我將它們稱為“南瓜香料”或“ PSM”。

Pumpkin Spice Metrics aid overall marketing activity by defining what typically happens during a seasonal sales period. The metrics themselves are not technologically different than the ones chosen for digital marketing campaigns or ones related to KPI (key performance indicators — metrics related to business objectives). The key value in establishing PSMs is to determine segments and activity based on the seasonal influences and campaign details that are known.

南瓜香料度量標準通過定義季節性銷售期間通常發生的情況來輔助總體營銷活動。 指標本身在技術上與為數字營銷活動選擇的指標或與KPI相關的指標(技術指標-與業務目標相關的指標)沒有技術差異。 建立PSM的關鍵價值是根據已知的季節性影響和活動詳細信息來確定細分和活動。

So where should a business start to plan effective measurement against the seasons, especially as shopping behavior has shifted?

那么,企業應該從哪里開始計劃針對季節的有效衡量標準,尤其是在購物行為發生變化時?

One clear starting point is just looking at what regional traffic has been typical. Different regions celebrate seasonal events in which businesses participate with promotions. This means more activity related to those events can appear in the analytics as increases from a local region.

一個明確的起點只是看區域交通的典型情況。 不同地區慶祝企業參加促銷活動的季節性活動。 這意味著與這些事件相關的更多活動可以隨著本地區域的增加而出現在分析中。

So imagine website visits associated with Los Angeles or Houston experiencing a rising count near the time of Cinco De Mayo, a celebration of Mexican culture and heritage. Both regions are home to the largest Hispanic populations in the United States, while a Wikipedia post on Cinco De Mayo notes that the celebration, originated in the southwestern region of the United States, is celebrated in large cities with large Mexican-American populations. Companies with products normally purchased near the May 5th date would review visits to see if they map to those locations, then decide where to best deploy advertising.

因此,想象一下在臨近Cinco De Mayo(慶祝墨西哥文化和遺產)的時期,與洛杉磯或休斯頓相關的網站訪問量正在上升。 這兩個地區都是美國最大的西班牙裔人口的家園,而維基百科上Cinco De Mayo的帖子則指出,這項慶祝活動起源于美國西南部地區,是在墨西哥裔美國人人口眾多的大城市中進行慶祝的。 購買產品通常在5月5日前后購買的公司會審核訪問,以查看它們是否映射到這些位置,然后決定在哪里最好地部署廣告。

There are several ways to do this in an analytics solution. The easiest is to set up a geolocation report in Google Analytics or Adobe Analytics. Chart the number of visits from a region in which the population is understood. Analysts usually examine the reports for a consistent number of visits, with signs of engagement, either by time spent on-site or by conversion rate.

在分析解決方案中,有幾種方法可以做到這一點。 最簡單的方法是在Google Analytics(分析)或Adobe Analytics中設置地理位置報告。 繪制來自了解人口的區域的訪問次數。 分析師通常根據在現場花費的時間或轉化率來檢查報告中是否有一致的訪問次數,并帶有參與的跡象。

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This Google Analytics Location Report breaks down visits according to state. California is the darkest because it has the most visits, followed by New York and Texas. That information is useful if marketing had planned for visits from those regions to rise during a build up period to a seasonal event.
此Google Analytics(分析)位置報告根據狀態細分了訪問次數。 加州是最黑暗的地區,因為訪問量最多,其次是紐約和德克薩斯州。 如果營銷計劃將那些地區的訪問量增加到季節性事件,則該信息將很有用。
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A geolocation report can be adjusted to view a metro area, helpful for more nuance.
可以調整地理位置報告以查看都會區,這有助于產生更多細微差別。

A quick aside: Conversion rate is the percentage of visitors who complete a given activity on your site. This metric is set in the analytics manually in the goals setting.

簡單來說:轉化率是完成您網站上給定活動的訪問者的百分比。 該指標是在目標設置中的分析中手動設置的。

Another key analysis is using time as a demarcation between a seasonal period and time leading up to the season. Search patterns can change between a season and lead up period to the season. Marking the time periods can reveal search patterns allowing you to ask “Are there any keywords or phrases that are appearing regularly before the season?” Those words may be opportunities to adjust paid search ads or content ideas for a blog associated with a site. While hashtags are meant for social media, tweets and Pinterest pins can appear in search results. Thus the ideas from a search report can spark research ideas for hashtags as well. The end result for this exercise is to develop a list of content ideas that fits the seasons, the phrases that customers are collectively speaking.

另一個關鍵分析是將時間用作季節與季節之間的分界。 搜索模式可以在一個季節之間以及該季節的準備期之間變化。 標記時間段可以顯示搜索模式,使您可以問:“在該季節之前是否有規律出現的關鍵字或詞組?” 這些詞可能是調整與網站關聯的博客的付費搜索廣告或內容創意的機會。 盡管標簽是用于社交媒體的,但推文和Pinterest固定圖釘可能會出現在搜索結果中。 因此,搜索報告中的構想也可以激發主題標簽的研究構想。 此練習的最終結果是開發出適合季節的內容創意列表,即客戶共同說出的短語。

In the instance of the fall retail seasons (Halloween, Thanksgiving, Christmas) you can look at search patterns from the time the pandemic began to the present. Comparing the search pattern from last year to this year can reveal if a past strategy will not be as effective for this year. That can make a difference in where to spend a digital ad budget or marketing resources.

在秋季零售季節(萬圣節,感恩節,圣誕節)的情況下,您可以查看從大流行開始到現在的搜索模式。 比較去年和今年的搜索模式,可以發現過去的策略今年是否會不那么有效。 這可能會影響數字廣告預算或營銷資源的支出位置。

Businesses can consider PSMs as a factor in modeling advanced analytics, such as forecast modeling. But the behavioral differences people are exhibiting while social distancing means that a model may not be work as effectively as it would have given a standard retail year. It may be better to see if advanced modeling can be used for the next season.

企業可以將PSM作為建模高級分析(例如預測建模)的一個因素。 但是,人們在社交疏遠時表現出的行為差異意味著該模型可能無法像給定的標準零售年份那樣有效。 最好看看下一個賽季是否可以使用高級建模。

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Would a launch of a pumpkin spice cereal create extra demand for milk? A market basket analysis would help a grocer determining if it should plan a promotion with milk and cereal.
推出南瓜香料谷物會增加牛奶需求嗎? 市場購物籃分析將幫助雜貨商確定是否應計劃用牛奶和谷物促銷。

One advanced technique that can be used is a basket analysis. This analysis identifies the likelihood that one or more items are purchased alongside another item. A toothbrush alongside a toothpaste or mouthwash may make sense, but there could be other products that trigger the sales. The result from an analysis are suggestions for how products are mentioned on website pages, app pages, or in value coupons. Even having them appear alongside in a video would be helpful.

可以使用的一種先進技術是籃分析。 該分析確定了與另一個項目一起購買一個或多個項目的可能性。 牙刷與牙膏或漱口水一起使用可能很有意義,但可能還有其他產品觸發了銷售。 分析的結果是有關如何在網站頁面,應用程序頁面或價值優惠券中提及產品的建議。 即使讓它們出現在視頻中也會很有幫助。

The time period discovered for seasonal sales can be a starting point for this analysis.

發現季節性銷售的時間段可以作為此分析的起點。

Overall, you just can’t be prepared for a seasonal event without the right strategy. Identifying the pumpkin spice metrics in your business is the right strategy of creating sweet campaign ideas from seasonal customer interest.

總體而言,如果沒有正確的策略,您只是無法為季節性活動做好準備。 在您的業務中確定南瓜香料的度量標準是根據季節性客戶興趣創建甜美廣告活動想法的正確策略。

翻譯自: https://medium.com/@ZimanaAnalytics/pumpkin-spice-metrics-psm-how-to-plan-seasonal-advertising-8745bdbfe192

r psm傾向性匹配

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