Built in the U.S. for practical customer data growth.立足美国，专注实用型客户数据增长。

DataGive helped us turn old order records into usable customer profiles. We were able to contact more past buyers for feedback, product education, and repeat-purchase campaigns without rebuilding our data from zero.

DataGive 帮我们把老订单记录变成了可用客户资料。我们可以联系更多历史买家做反馈、产品教育和复购活动，不需要从零重建数据。

For a local service business, the hardest part is knowing which households to reach first. The ZIP-code and homeowner filters made our outreach more focused and reduced wasted calls.

对本地服务商来说，最难的是先找出应该触达哪些家庭。邮编和房主筛选让我们的触达更聚焦，也减少了无效外呼。

We uploaded a partial customer file and got back a much cleaner contact list. The output was easy to import into our CRM, and the team could start campaigns quickly.

我们上传了一份不完整的客户文件，返回结果明显更完整、更干净。输出文件很容易导入 CRM，团队可以很快启动营销活动。

As an agency, we need practical data that clients can understand. DataGive made it easier to explain targeting logic, expected fields, and how the list would be used in campaigns.

作为代理商，我们需要客户能理解的实用数据。DataGive 让我们更容易解释筛选逻辑、输出字段，以及这些名单如何用于营销活动。

The audience filters were useful for finding people who matched our product category. It gave us a better starting point for sampling and product education than broad advertising alone.

人群筛选对寻找匹配我们产品品类的人很有帮助。相比单纯投放广告，它给了我们更好的试用和产品教育起点。

The phone append results helped our team prioritize follow-up. Instead of spending hours searching for missing numbers, we had a structured file ready for outbound workflows.

电话附加结果帮助我们的销售团队更好地安排跟进。不需要花大量时间手动查找号码，直接拿到结构化文件就能进入外呼流程。

Recent movers are a very practical segment for us. The list helped us design campaigns around move-in services, local offers, and neighborhood introductions.

最近搬家者对我们来说是非常实用的人群。名单帮助我们围绕入住服务、本地优惠和社区介绍来设计营销活动。

The homeowner and property-related filters were exactly what we needed. We used the data to narrow our direct mail area and focus on higher-value households.

房主和房产相关筛选正是我们需要的。我们用这些数据缩小直邮区域，把预算集中在价值更高的家庭上。

For solar outreach, not every household is a good fit. DataGive helped us filter by property and location signals before calling, which made the list more practical.

做太阳能触达时，并不是每个家庭都合适。DataGive 帮我们先按房产和地区信号筛选，再去外呼，名单更实用。

We used appended contact data to follow up with customers after purchase. It worked well for support reminders, warranty communication, and education around product usage.

我们用附加联系方式对购买后的客户进行跟进。它很适合售后提醒、保修信息沟通和产品使用教育。

The automotive audience filters gave us a more focused way to reach likely buyers. It was useful for product testing and for building remarketing lists around specific categories.

汽配人群筛选让我们更精准地触达潜在买家。它对产品测试和围绕细分品类建立再营销名单很有价值。

We needed a better audience for pet product sampling. The household and pet-related signals helped us avoid overly broad lists and focus on people more likely to respond.

我们需要更好的宠物产品试用人群。家庭和宠物相关信号帮助我们避免名单过泛，聚焦更可能响应的人。

For local course promotion, the family and geography filters were helpful. We could focus on the right neighborhoods instead of sending the same message everywhere.

做本地课程推广时，家庭和地区筛选很有帮助。我们可以聚焦合适社区，而不是把同一条信息发给所有人。

The household profile filters gave us a clearer starting point for outreach. It helped us prepare more relevant messages for different income and life-stage segments.

家庭画像筛选给了我们更清晰的触达起点。我们可以根据收入和人生阶段准备更相关的话术。

What I like most is that the output is practical. The file structure is easy to understand, and our team does not need extra training before importing it into tools.

我最喜欢的是输出结果足够实用。文件结构清晰，团队不需要额外培训就能导入工具使用。

DataGive is helpful when a client has a marketing idea but no clear audience. We can quickly turn the idea into filters, lists, and a real execution plan.

当客户有营销想法但没有清晰人群时，DataGive 很有帮助。我们可以快速把想法转化为筛选条件、名单和可执行方案。

We used Data Append to improve post-purchase follow-up. It gave us more ways to reach real customers for feedback, instructions, and product experience questions.

我们用数据附加改善售后跟进。它让我们有更多方式联系真实客户，获取反馈、发送说明和了解产品体验。

The enrichment workflow saved time for our small sales team. We could focus on messaging and qualification instead of manually completing contact fields.

补全流程为我们的小销售团队节省了时间。我们可以把精力放在话术和筛选上，而不是手动补全联系方式。

For store promotions, location-based targeting was very useful. We created smaller, cleaner lists around the areas that actually mattered to each campaign.

对门店促销来说，基于地区的定向非常有用。我们围绕每次活动真正重要的区域，创建了更小、更干净的名单。

We used the data for a membership trial campaign. The audience was more relevant than our previous broad lists, and the team felt more confident reaching out.

我们把数据用于会员试用活动。相比之前的泛名单，这批人群更相关，团队在触达时也更有信心。

The delivered file was clean enough for analysis and CRM import. Having consistent columns for contact fields and audience attributes made downstream work easier.

交付文件足够干净，方便分析和导入 CRM。联系方式和人群属性字段保持一致，让后续工作轻松很多。

We combined email, direct mail, and phone follow-up using the same audience foundation. It helped us keep messaging more consistent across channels.

我们基于同一批人群，同时做邮件、直邮和电话跟进。这样跨渠道信息更加一致，也更容易管理。